Do Functional Limitations Predict Life Satisfaction Among Older Adults in India: A Study based on LASI Survey in India

Do Functional Limitations Predict Life Satisfaction Among Older Adults in India: A Study based on LASI Survey in India | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Do Functional Limitations Predict Life Satisfaction Among Older Adults in India: A Study based on LASI Survey in India Shekhar Chauhan, Pradeep Kumar, Shobhit Srivastava, Ratna Patel This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-721491/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Functional limitation is a relevant health outcome to examine the quality of life among the elderly. In recognition of its importance, research evidence evaluating life satisfaction among older people has increased globally, but such research is minimalistic in the Indian context. Furthermore studies in the Indian context examining life satisfaction among the elderly population in the context of ADL and IADL are hard to find. Therefore, this study examines the association between functional limitations and life satisfaction among the older population in India. Methods: Data for this study was utilized from the recent release of Longitudinal Ageing Study in India (LASI) wave 1. The total sample size for the present study is 31,464 older adults aged 60 years and above. Life satisfaction was the main dependent variable categorized as 0 “high,” 1 “medium,” and 2 “low.” Descriptive statistics, along with bivariate analysis, was used to present the preliminary analysis. Apart from that, the ordered logistic regression analysis was used to carve out the results. Results: Overall, about one-third of older adults had low life satisfaction scores, and 46% of older adults had a high life satisfaction score. The low life satisfaction score was higher among older adults who reported poor self-rated health (36.7%) than those who reported good self-rated health (27.9%). For older adults who were independent for ADL, the odds of low life satisfaction score (LSS) versus the combined medium and high LSS were 1.20 times more than for older adults who were not independent for ADL [UOR: 1.20; CI: 1.14-1.26]. Conclusion: In this study, a possible association between functional limitations and life satisfaction among the elderly was explored. Both ADL and IADL were noted as factors determining life satisfaction among elderly and elderly reporting ADL and IADL had higher odds of LLS. The setting up of geriatric clinics under the Primary Health Care services would bring the necessary change as this would provide timely healthcare services to the elderly and generate a perception of overall satisfaction among the elderly as they may feel secure in the presence of better health infrastructure. Geriatrics & Gerontology Functional limitations ADL IADL Older people India Background: Over the years, India has witnessed an unprecedented growth in population resulting from higher fertility rates across India [1]. However, the decline in fertility rates in recent times has brought down the country's population growth rate [2]. With the declining growth rate in recent years, a new issue on population dynamics has arisen, i.e., the ageing population. A decline in fertility rates coupled with increased life expectancy has led to a rise in ageing population [3]. Improving education, health facilities, and life expectancy has led to an increase in the proportion of the elderly population in India, and the share of the elderly population has increased from 5.3 percent in 1971 to 5.7 percent in 1981 and further from 6 percent in 1991 to 8 percent in 2011 [4]. Moreover, by 2050, the share of the 60 + population is projected to climb 19 percent, or approximately 323 million people in India [5]. Increasing life expectancy adds more life to years and adds disabilities to the life years among the elderly [6]. The ageing process implies a higher probability of suffering from disease and disability [5], [7]. The ageing process not only affects the household headship [8] but also has been widely associated with chronic diseases [7], low psychological health [9], [10], low subjective well-being [9], [10], poor self-rated health [11], and life satisfaction [12]. Life satisfaction is an important universal objective and measurement of quality of life [13]. Life satisfaction among the elderly is a critical aspect of the psychological dimension that has proved association with positive health behaviours [14], better physical and mental health outcomes [15], and successful ageing [16]. Moreover, life satisfaction is a general measure of overall wellbeing that measures the degree of coherence between life dreamed of and the life achieved [17]. Various factors have been linked to life satisfaction among the elderly, including social support [18], living arrangement [18], marital status [19], and demographic factors [20]–[22]. Functional limitations as measured through Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) have also been linked to life satisfaction among the elderly [18]. Functional limitation/disability is a relevant health outcome to examine the quality of life among the elderly [23]. Disability can be examined in several ways; however, using ADL and IADL to measure disability is one of the most popular and widely used tools [24]. ADL functions are more concerned with an individual’s self-care, whereas IADL functions are more concerned with self-reliant functioning in daily life [25]. Studies have noted that ADL disability presents greater difficulties and is a severe form of disability than IADL disability [26], [27]. Several previous studies were conducted examining associated factors of functional limitations in ADL and IADL among the elderly [28]–[31]. Unfortunately, limited evidence was presented that examined the association between functional limitations and life satisfaction among the elderly [23]. A study in the Nigerian context examined the association between functional disability and quality of life; however, depression was also included as a covariate of quality of life and functional limitations [26]. Another study in Japan contextualized quality of life through ADL; however, the main focus was on the association between fear of falling and quality of life [32]. In recognition of its importance, research evidence evaluating life satisfaction among older people has increased globally [12], [33]–[36], but such research is minimalistic in the Indian context. Whatever limited research evaluating life satisfaction among the elderly in India is limited to various community settings [18], [21], [37], [38]. Furthermore, to the author’s best knowledge, none of the studies in the Indian context has examined life satisfaction among the elderly population in the context of ADL and IADL. In Indian society, older people are traditionally attended by their family members and are more likely to be satisfied with their lives [18]. During ageing, older people deal with ADL and IADL limitations, and therefore, it becomes seemingly stressful for them to remain satisfied with their life. Given the positive association between life satisfaction and an individual’s social support [14], and an inverse relationship between life satisfaction and solitude [33], this study becomes vital as it intends to examine life satisfaction through the lens of functional limitations among the elderly. Given the above background, an attempt has been made to explore the association between functional limitations and life satisfaction among the older population in India. The study also explored the association between socioeconomic and demographic characteristics with life satisfaction among the older population. The study hypothesizes that the elderly with ADL and IADL related functional disabilities would have Low Life Satisfaction (LLS), representing it vice-versa. Those without ADL and IADL related functional disabilities would have higher life satisfaction (HLS). Methods: Data source: Data for this study was utilized from the recent release of Longitudinal Ageing Study in India (LASI) wave 1 [39]. The LASI is a nationally representative survey of over 72000 older adults aged 45 and above across India's states and union territories [39]. The survey adopted a three-stage sampling design in rural areas and a four-stage sampling design in urban areas. In each state/UT, the first stage involved the selection of Primary Sampling Units (PSUs), that is, sub-districts (Tehsils/Talukas), and the second stage involved the selection of villages in rural areas and wards in urban areas in the selected PSUs [39]. In rural areas, households were selected from selected villages in the third stage [39]. However, sampling in urban areas involved an additional stage. Specifically, in the third stage, one Census Enumeration Block (CEB) was randomly selected in each urban area [39]. In the fourth stage, households were selected from this CEB [39]. The detailed methodology, with the complete information on the survey design and data collection, was published in the survey report [39]. The present study is conducted on eligible respondents aged 60 years and above. The total sample size for the present study is 31,464 older adults aged 60 years and above. The Indian Council of Medical Research (ICMR) extended the necessary guidance and ethical approval for conducting the LASI [39]. Variable description Outcome variable Life satisfaction among older adults was assessed using the questions a. In most ways, my life is close to ideal; b. The conditions of my life are excellent; c. I am satisfied with my life d. So far, I have got the important things I want in life; e. If I could live my life again, I would change almost nothing. The responses were categorized as strongly disagree, somewhat disagree, slightly disagree, neither agree nor disagree, slightly agree, somewhat agree, and strongly agree. Using the responses to the five statements regarding life satisfaction, a scale was constructed. The categories of the scale are ‘low satisfaction’ (score of 5–20), ‘medium satisfaction’ (score of 21–25), and ‘high satisfaction’ (score of 26–35) [39]. The outcome variable was coded as 0 “high,” 1 “medium,” and 2 “low.” Control variable Main control variables Difficulty in ADL (Activities of Daily Living) was coded as no and yes. Activities of Daily Living (ADL) is a term used to refer to normal daily self-care activities (such as movement in bed, changing position from sitting to standing, feeding, bathing, dressing, grooming, personal hygiene, etc.) The ability or inability to perform ADLs is used to measure a person’s functional status, especially in the case of people with disabilities and older adults [40], [41]. Difficulty in IADL (Instrumental Activities of Daily Living) was coded as no and yes. Instrumental activities of daily living are not necessarily related to the fundamental functioning of a person, but they let an individual live independently in a community. The set ask were necessary for independent functioning in the community. Respondents were asked if they were having any difficulties that were expected to last more than three months, such as preparing a hot meal, shopping for groceries, making a telephone call, taking medications, doing work around the house or garden, managing money (such as paying bills and keeping track of expenses), and getting around or finding an address in unfamiliar places [40], [41]. Individual control variables Age was categorized as young old (60–69 years), old-old (70–79 years), and oldest-old (80 + years) [42]. Sex was coded as male and female. Educational status was categorized as no education/primary not completed, primary, secondary, and higher [42]. Living arrangement was categorized as living alone, living with a spouse, living with children, and living with others. Marital status was categorized as currently married, widowed, and others [42]. Others included separated/divorced/never married. Working status was categorized as currently working, retired, and not working [9]. Active community involvement in life: Respondents were said to be socially engaged if they participate in the following activities. Eat out of house (Restaurant/Hotel); Go to park/beach for relaxing/entertainment; Play cards or indoor games; Play outdoor games/sports/exercise/jog/yoga; Visit relatives /friends; Attend cultural performances /shows/Cinema; Attend religious functions /events such as bhajan/satsang/prayer; Attend political/community/organization group meetings; Read books/newspapers/magazines; Watch television/listen radio and use a computer for e-mail/net surfing etc. If the respondent was involved in any of the above activities, the respondent was defined as socially engaged or involved in the community. Self-rated health was coded as good which includes excellent, very good, and good, where as poor includes fair and poor [11]. Psychological distress was coded as low, medium and high. Psychological distress was measured using the following questions a. How often did you have trouble concentrating? b. How often did you feel depressed? c. How often did you feel tired or low in energy? d. How often were you afraid of something? e. How often did you feel you were overall satisfied? f. How often did you feel alone? g. How often were you bothered by things that don’t usually bother you? h. How often did you feel that everything you did was an effort? i. How often did you feel hopeful about the future? j. How often did you feel happy? The response was coded as 1. Rarely or never 2. Sometimes 3. Often and 4. Most or all of the time. The response was coded as per the question in binary form 0 “Rarely or never/ Sometimes” and 1 “Often/ Most or all of the time” (Cronbach alpha: 0.70) [40]. Household control variables The monthly per-capita consumer expenditure (MPCE) quintile was assessed using household consumption data. Sets of 11 and 29 questions on the expenditures on food and non-food items, respectively, were used to canvas the sample households. Food expenditure was collected based on a reference period of seven days, and non-food expenditure was collected based on reference periods of 30 days and 365 days. Food and non-food expenditures have been standardized to the 30-day reference period. The monthly per capita consumption expenditure (MPCE) is computed and used as the summary measure of consumption. The variable was then divided into five quintiles, i.e., from poorest to richest [39]. Religion was coded as Hindu, Muslim, Christian, and Others. Caste was recoded as Scheduled Tribe, Scheduled Caste, Other Backward Class, and others [43], [44]. The Scheduled Caste includes “untouchables,”; a group of the population that is socially segregated and financially/economically by their low status as per Hindu caste hierarchy. The Scheduled Castes (SCs) and Scheduled Tribes (STs) are among India's most disadvantaged socio-economic groups. The OBC is the group of people who were identified as “educationally, economically and socially backward.” The OBC’s are considered low in the traditional caste hierarchy but are not considered untouchables. The “other” caste category is identified as having higher social status [44]. The place of residence was categorized as rural and urban. The region was coded as North, Central, East, Northeast, West, and South [45]. Statistical analysis Descriptive statistics, along with bivariate analysis, was used to present the preliminary analysis. Apart from that, the ordered logistic regression analysis was used to carve out the results. The dependent variables were ordered as 0 “high,” 1 “medium,” and 2 “low.” The ordered logit model is a regression model for an ordinal response variable. The model is based on the cumulative probabilities of the response variable. In particular, the logit of each cumulative probability is assumed to be a linear function of the covariates with regression coefficients constant across Response Categories [46]. All the methods were performed in accordance with the relevant guidelines and regulations laid down by the Declaration of Helsinki. Results: Table 1 presents socio-economic profile of older adults in India, 2017-18. About one-fourth of older adults were not fully independent for ADL, and nearly half of the older adults were not independent for IADL. More than half of the older adults belonged to the young-old cohort, 68 per cent of older adults had no education/primary not completed, and six per cent of older adults were living alone. Three-fifth of older adults were currently married, nearly one-third of older adults were working, and only nine per cent of older adults had community involvement. About 47 per cent of older adults reported poor self-rated health, and 29 per cent of older adults had high psychological distress. A higher proportion of older adults were Hindu, belonged to the OBC caste group, and lived in rural areas. Table 1 Socio-economic profile of older adults in India, 2017-18 Background characteristics Sample Percentage Difficulty in ADL No 23,802 75.7 Yes 7,662 24.4 Difficulty in IADL No 16,130 51.3 Yes 15,334 48.7 Age Young-old 18,410 58.5 Old-old 9,501 30.2 Oldest-old 3,553 11.3 Sex Male 14,931 47.5 Female 16,533 52.6 Education No education/primary not completed 21,381 68.0 Primary completed 3,520 11.2 Secondary completed 4,371 13.9 Higher and above 2,191 7.0 Living arrangement Living alone 1,787 5.7 Living with spouse 6,397 20.3 Living with children 21,475 68.3 Living with others 1,805 5.7 Marital status Currently married 19,391 61.6 widowed 11,389 36.2 Others 684 2.2 Working status Working 9,680 30.8 Retired 13,470 42.8 Not working 8,314 26.4 Community involvement No 28,545 90.7 Yes 2,919 9.3 Self-rated health Good 16,582 52.7 Poor 14,882 47.3 Psychological distress Low 12,135 38.6 Medium 10,216 32.5 High 9,114 29.0 MPCE quintile Poorest 6,829 21.7 Poorer 6,831 21.7 Middle 6,590 21.0 Richer 6,038 19.2 Richest 5,175 16.5 Religion Hindu 25,871 82.2 Muslim 3,548 11.3 Christian 900 2.9 Others 1,145 3.6 Caste Scheduled Caste 5,949 18.9 Scheduled Tribe 2,556 8.1 Other Backward Class 14,231 45.2 Others 8,729 27.7 Place of residence Rural 22,196 70.6 Urban 9,268 29.5 Region North 3,960 12.6 Central 6,593 21.0 East 7,439 23.6 Northeast 935 3.0 West 5,401 17.2 South 7,136 22.7 Total 31,464 100.0 Table 2 shows the percentage of older adults with high, medium, and low life satisfaction by background characteristics. Overall, about one-third of older adults had low life satisfaction scores, and 46% of older adults had a high life satisfaction score. Difficulty in ADL and IADL had a significant association with life satisfaction among older adults. For example, older adults who were not independent for ADL (37%) and IADL (35%) had a more low life satisfaction score than their counterparts. The low life satisfaction score was higher among older females than older males (33.8% vs. 30.4%). A negative association was observed between low life satisfaction scores and the educational level of older adults. Moreover, older adults who lived alone had more low life satisfaction score (47.8%). A low life satisfaction score was significantly higher among older adults who had community involvement (44.1%) than those who had no community involvement (31%). The low life satisfaction score was higher among older adults who reported poor self-rated health (36.7%) than those who reported good self-rated health (27.9%). Older adults who had high psychological stress reported more low life satisfaction score (47.2%). Similar to education, low life satisfaction scores among older adults had a significant negative association with the MPCE quintile. Low life satisfaction scores were more prevalent among older adults who belonged to scheduled caste/scheduled tribe. Moreover, older adults who lived in rural areas reported higher low life satisfaction scores compared to those who lived in urban areas (34.4% vs. 26.7%). Table 2 Percentage of older adults with High, Medium and Low life satisfaction by their background characteristics in India, 2017-18 Background characteristics Life satisfaction p-value High Medium Low Difficulty in ADL 0.001 No 47.1 22.2 30.8 Yes 40.1 22.9 37.0 Difficulty in IADL 0.001 No 49.0 21.8 29.2 Yes 41.6 22.9 35.4 Age 0.352 Young-old 45.5 22.8 31.7 Old-old 46.0 21.2 32.8 Oldest-old 44.0 23.0 33.1 Sex 0.001 Male 47.2 22.5 30.4 Female 44.0 22.3 33.8 Education 0.001 No education/primary not completed 39.9 23.4 36.8 Primary completed 49.8 22.0 28.2 Secondary completed 60.2 19.6 20.3 Higher and above 63.7 19.0 17.3 Living arrangement 0.001 Living alone 32.9 19.4 47.8 Living with spouse 45.3 23.1 31.6 Living with children 47.3 22.5 30.3 Living with others 36.7 21.2 42.2 Marital status 0.001 Currently married 47.4 22.9 29.7 widowed 43.0 21.4 35.7 Others 32.7 23.2 44.1 Working status 0.001 Working 44.4 23.7 31.9 Retired 46.2 21.3 32.4 Not working 45.6 22.4 32.0 Community involvement 0.001 No 46.2 22.7 31.0 Yes 37.6 18.3 44.1 Self-rated health 0.001 Good 50.8 21.3 27.9 Poor 39.8 23.5 36.7 Psychological distress 0.001 Low 62.2 19.0 18.8 Medium 42.8 24.1 33.1 High 28.5 24.4 47.2 MPCE quintile 0.001 Poorest 37.6 24.0 38.4 Poorer 43.0 22.9 34.1 Middle 46.9 22.9 30.3 Richer 49.7 21.9 28.4 Richest 52.5 19.3 28.2 Religion 0.001 Hindu 45.6 22.2 32.2 Muslim 43.5 23.9 32.7 Christian 44.5 19.5 36.0 Others 49.7 23.9 26.4 Caste 0.001 Scheduled Caste 37.5 23.1 39.4 Scheduled Tribe 39.8 23.1 37.1 Other Backward Class 46.5 21.9 31.6 Others 50.9 22.5 26.7 Place of residence 0.001 Rural 42.2 23.5 34.4 Urban 53.7 19.6 26.7 Region 0.001 North 41.9 24.3 33.8 Central 41.8 25.5 32.7 East 37.6 25.9 36.5 Northeast 45.2 28.7 26.1 West 68.6 15.3 16.1 South 41.6 19.1 39.4 Total 45.5 22.4 32.2 p-value based on chi-square test Estimates from ordered logistic regression analysis for life satisfaction among older adults are presented in Table 3 . Model 1 shows unadjusted odds ratio for life satisfaction whereas Model 2 provides the adjusted (odds ratio) estimates for life satisfaction. For older adults who were independent for ADL, the odds of low life satisfaction score (LSS) versus the combined medium and high LSS were 1.20 times more than for older adults who were not independent for ADL [UOR: 1.20; CI: 1.14–1.26]. Likewise, the odds of combined categories of low and medium LSS versus high LSS was 1.20 times higher for those who were independent for ADL than those who were not independent. However, this result was not significant in adjusted model 2. The odds of difficulty in IADL decreased from unadjusted to adjusted model. For older adults who had difficulty in IADL, the odds of low LSS versus the combined medium and high LSS were 1.13 times higher than for older adults who had not difficulty in IADL [AOR: 1.13; CI: 1.08–1.19]. Likewise, the odds of combined categories of low and medium LSS versus high LSS was 1.13 times higher for those who had difficulty in IADL than those who did not have. For female, the odds of low LSS versus the combined medium and high LSS were 0.94 times lower than for males. Similarly, the odds of the combined categories of low and medium LSS versus high LSS was 0.94 times lower for females compared to males. For older adults with higher education, the odds of low LSS versus the combined medium and high LSS were 1.31 times higher than for those who had no education. Likewise, the odds of the combined categories of low and medium LSS versus high LSS was 1.31 times higher for older adults with higher education compared to those who had no education. Moreover, for older adults who lived in rural areas, the odds of low LSS versus the combined medium and high LSS were 1.11 times higher than for those who lived in urban areas. Likewise, the odds of the combined categories of low and medium LSS versus high LSS was 1.11 times higher for older adults living in rural areas compared to those who lived in urban areas. Table 3 Ordered logistic regression estimates for life satisfaction among older adults in India, 2017-18 Background characteristics Model-1 Model-2 UOR (CI) AOR (CI) Difficulty in ADL No Ref. Ref. Yes 1.20*(1.14,1.26) 0.98(0.92,1.04) Difficulty in IADL No Ref. Ref. Yes 1.41*(1.35,1.47) 1.13*(1.08,1.19) Age Young-old Ref. Old-old 0.93*(0.89,0.98) Oldest-old 0.81*(0.75,0.88) Sex Male Ref. Female 0.94*(0.89,0.99) Education No education/primary not completed Ref. Primary completed 1.94*(1.76,2.15) Secondary completed 1.60*(1.44,1.79) Higher and above 1.31*(1.18,1.45) Living arrangement Living alone 1.27*(1.10,1.46) Living with spouse 0.90(0.80,1.02) Living with children 0.86*(0.77,0.96) Living with others Ref. Marital status Currently married Ref. widowed 0.96(0.91,1.02) Others 1.07(0.93,1.24) Working status Working Ref. Retired 0.93*(0.88,0.98) Not working 0.89*(0.83,0.96) Community involvement No Ref. Yes 1.05(0.97,1.14) Self-rated health Good Ref. Poor 1.32*(1.26,1.38) Psychological distress Low Ref. Medium 1.92*(1.82,2.03) High 2.99*(2.82,3.16) MPCE quintile Poorest 1.31*(1.21,1.41) Poorer 1.13*(1.05,1.22) Middle 1.10*(1.02,1.18) Richer 1.06(0.98,1.14) Richest Ref. Religion Hindu Ref. Muslim 1.16*(1.08,1.24) Christian 0.93(0.85,1.02) Others 0.95(0.85,1.06) Caste Scheduled Caste 1.20*(1.12,1.29) Scheduled Tribe 1.18*(1.09,1.28) Other Backward Class 0.99(0.93,1.05) Others Ref. Place of residence Rural 1.11*(1.05,1.17) Urban Ref. Region North Ref. Central 1.01(0.94,1.1) East 1.35*(1.26,1.46) Northeast 1.05(0.96,1.16) West 0.50*(0.46,0.54) South 1.19*(1.11,1.28) /cut1 -0.02(-0.05,0.01) 1.02(0.86,1.18) /cut2 0.97*(0.94,0.99) 2.13*(1.96,2.29) Ref: Reference; *if p < 0.05; UOR: Unadjusted odds ratio; AOR: Adjusted odds ratio; CI: Confidence interval; Life satisfaction: 0 "High:, 1 "medium" and 2 "low". Discussion: By examining the association between functional disability and life satisfaction among the elderly, this study addressed the long-standing gap in the literature. Previously, minimal literature has examined the association between functional disability and life satisfaction [47]–[49], and such studies from the Indian context are somewhat more limited [18]. Banjare et al. (2015) examined determinants associated with life satisfaction among the elderly in rural Odisha, and they did not exclusively examine the association between functional limitation and life satisfaction; rather, they included the functional limitation as a general predictor of life satisfaction [18]. Therefore, the current study fills the research gap to a great extent while examining the association between functional disability and life satisfaction among the elderly. The findings noted support for our hypothesis that those with ADL and IADL related functional disabilities would have Low Life Satisfaction (LLS). The unadjusted and adjusted model findings noted higher odds of LLS among elderly with ADL and IADL related functional limitations. These findings agree with previously available literature [18], [50]. Occurrence of functional limitations bound elderly to the home [51], cut their personal ties [52], and limit their physical activity [53], which could be associated with lower life satisfaction among them. Functional limitations reduce the ability to move and reduce participation in social activities and social contacts, leading to a decline in life satisfaction among the elderly. The odds of LLS were lower among the oldest-old than the young-old elderly, which deviates from the findings of several previous studies [49], [54], [55]. This study specifically noted higher chances of low life satisfaction among young-old than oldest old. Generally, it is assumed that as age increases, the odds of low life satisfaction among the elderly would decrease due to the onset of several chronic conditions and change in living arrangement; however, the findings in this study are somewhat different. A study in the Chinese context corroborated the findings of this study and noted that older individuals had a higher level of life satisfaction than their younger counterparts [56]. The finding of lower odds of LLS among the oldest-old is compatible with a phenomenon known as the paradox of ageing [57], [58]. The paradox of ageing relates to the notion that older people tend to react less to adverse situations, ignore irrelevant negative stimuli better, and remember relatively more positive information than negative information [57], leading to higher life satisfaction. Also, older people are more likely to derive emotional satisfaction from prioritizing positive information processing [58], which could have also linked to higher life satisfaction among the oldest elderly. To add more, a study noted that older people tend to use less interpersonal comparisons than younger people, positively affecting their life satisfaction [59]. The odds of LLS were lower among female elderly than their male counterparts, implying that the satisfaction level was higher among female elderly than in male elderly. Previous studies reported mixed findings where certain studies noted higher life satisfaction among male elderly [60], whereas few other studies noted higher life satisfaction among female elderly [12], [61], [62]. Older women are more likely to seek healthcare in India [63], partially explaining their higher life satisfaction. Furthermore, women enjoy an advantage in adapting to old age complications over men [64], which could also explain the higher life satisfaction among older women than older men. However, the odds of LLS were declining with the increase in the educational status of the elderly; this study noted higher odds of LLS for each class of educated elderly than non-educated elderly. In general, education is positively linked to life satisfaction in previous literature [9], [55], [65]. However, quite a few studies noted similar results as in this study [60], [66]. A possible mechanism that links education to job satisfaction and further to life satisfaction may partially explain the higher life satisfaction among educated elderly [67], [68]. It explains that those with higher education would find a job that fits better to their skills and abilities, leading to higher life satisfaction. However, this study noted an otherwise result where odds of LLS were higher among educated elderly. There could be a few plausible mechanisms for the same in this study. First, individuals with lower levels of education may be easily satisfied with their current simple living conditions in contrast to educated elderly still having some unsatisfied needs in their life [56]. Educated elderly might be working before getting retired, and after retirement, they might be feeling a sudden change in their environment and lifestyle, which may partially explain the status of life satisfaction among them. Moreover, pension status after retirement plays an important role in depression among the elderly, which may also partially explain the life satisfaction among the elderly [69]; however, this study did not examine pension status and its association with life satisfaction among the elderly. Corroborating with several previous studies [70]–[72], this study also noted a higher odds of LLS among elderly living alone and lower odds of LLS among the elderly living with children. Living with children provides a sense of security and social support to the elderly and a sense of belongingness, which could be attributed to higher life satisfaction. Living with children provides social support that improves self-esteem, gives a purpose to live, and can rightly be attributed to higher life satisfaction. Family support has been positively linked to life satisfaction among the elderly [54]. Several research has presented evidence that financial support from children contributes to life satisfaction among the elderly [71], [73]. As expected, those who reported poor self-rated health and had high psychological distress had higher odds of LLS. This finding is in agreement with previously available literature in the Indian context [18], [74]–[78]. Elderly having poor psychological health are more prone to depression, which could further be linked to LLS [18]. Good health allows the elderly to maintain social contacts, resulting in a higher level of life satisfaction. The elderly in rural areas had higher odds of LLS, implying a higher life satisfaction among the urban elderly. Previous studies also noted a higher life satisfaction among the urban elderly [78]. The elderly in urban areas have greater access to medical services, which could be linked to higher life satisfaction [72]. Moreover, urban elderly have a greater awareness of their age-related outcomes, which can further be linked to higher life satisfaction [79]. The modern facilities, better infrastructure, and higher pension allowance in urban areas probably contributed to the higher life satisfaction among the urban elderly [12]. Limitations and strengths of the study: The study findings should be interpreted in the light of several limitations. One major challenge to perceive the well-being of older adults is to obtain reliable information on self-rated life satisfaction, as some oldest-old and old-old people may be suffering from loss of cognitive ability leading to ambiguity in the study results [80]. To a certain extent, possible biases in self-evaluation of life satisfaction may be driven by socio-economic factors. The cross-sectional nature of data limits our understanding of causality, and reverse causation is possible for study findings. Despite the above limitations, the study has certain noteworthy strengths too. The study is based on recently released data, therefore, providing the current estimates. Furthermore, the study findings can be generalized in a broader context as the data collected are nationally representative. The study measured life satisfaction with various items, therefore providing robust estimates than those studies where life satisfaction was measured with a single item [78]. Measuring life satisfaction with a single item may be influenced by the mood of the respondents during the interview and other situational factors, and therefore measuring life satisfaction with a set of items will always be a suggested way to examine life satisfaction [81]. At last, minimal research investigated the association between functional disability and life satisfaction among the elderly. This study could set things in motion for other researchers who may explore this association in their future studies. Conclusion: In this study, a possible association between functional limitations and life satisfaction among the elderly was explored, along with exploring other determinants of life satisfaction among the elderly in India using information from a nationally representative survey. Both ADL and IADL were noted as factors determining life satisfaction among elderly and elderly reporting ADL and IADL had higher odds of LLS. Other prominent factors determining life satisfaction among the elderly include higher age, female gender, living with children, good self-rated health, low psychological distress, and urban residence. This study focuses on functional limitations and life satisfaction among the elderly and certainly has some policy suggestions. Addressing psychological distress among the elderly could be a game-changer in providing a sense of satisfaction among the elderly, and to achieve this, there is a need to strengthen the quality of care delivered to older people. The setting up of geriatric clinics under the Primary Health Care services would bring the necessary change as this would provide timely healthcare services to the elderly and generate a perception of overall satisfaction among the elderly as they may feel secure in the presence of better health infrastructure. Since living with children enhances life satisfaction among the elderly, more stress should be laid upon the counseling among the younger generation, which can encourage them to support and look after the needs of their elderly as it would improve further lead to life satisfaction among the elderly [18]. At last, focus needs to be aimed at the elderly who are not independent for ADL and IADL functions and are suffering from severe functional limitations. Abbreviations ADL: Activity of Daily Living IADL: Instrumental Activity of Daily Living LASI : Longitudinal Ageing Study in India CI: Confidence Interval UOR: Unadjusted Odds Ratio OR: Odds Ratio LLS: Low Life Satisfaction HLS: High Life Satisfaction Declarations Ethics approval and consent to participate: The data is freely available on request and survey agencies that conducted the field survey for the data collection have collected a prior consent from the respondent. The ethical clearance was provided by Indian Council of Medical Research (ICMR), India. Moreover, participants were provided with the information brochures explaining the purpose of the survey, ways of protecting their privacy, and safety of the health assessments as part of the ethics protocols. Consent for publication: Not applicable Availability of data and materials: The datasets generated and/or analysed during the current study are available with the International Institute for Population Sciences, Mumbai, India repository and could be accessed from the following link: https://iipsindia.ac.in/sites/default/files/LASI_DataRequestForm_0.pdf. Those who wish to download the data have to follow the above link. This link leads to a data request form designed by International Institute for Population Sciences. After completing the form, it should be mailed to: [email protected] for further processing. After successfully sending the mail, individual will receive the data in a reasonable time. Competing Interest: The authors declare that they have no competing interests. Funding: Authors did not receive any funding to carry out this research. Author’s Contribution: The concept was drafted by SC and RP. SS and PK contributed to the analysis design. SC advised on the paper and assisted in paper conceptualization. SC and RP contributed in the comprehensive writing of the article. All authors read and approved the final manuscript. Acknowledgements: Not applicable References P. M. Kulkarni and M. Alagarajan, “Population Growth, Fertility, and Religion in India,” Economic and Political Weekly , vol. 40, no. 5, pp. 403–410, 2005, doi: https://www.jstor.org/stable/4416131 . D. E. Bloom, Population Dynamics in India and Implications for Economic Growth . Oxford University Press, 2012. doi: 10.1093/oxfordhb/9780199734580.013.0015 . S. Chauhan and P. Arokiasamy, “India’s demographic dividend: state-wise perspective,” Journal of Social and Economic Development , vol. 20, no. 1, pp. 1–23, 2018. R. Patel, S. Chauhan, D. Chaurasiya, S. Kumar, and B. Paswan, “Role and Impact of Social Capital on Health of Older Adult in India,” Indian Journal of Social Research , vol. 60, no. 2, pp. 279–305, 2019. A. Agarwal, A. Lubet, E. Mitgang, S. Mohanty, and D. E. Bloom, “Population aging in India: Facts, issues, and options,” in Population change and impacts in Asia and the Pacific , Springer, 2020, pp. 289–311. C. J. L. Murray et al. , “Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010,” The Lancet , vol. 380, no. 9859, pp. 2197–2223, Dec. 2012, doi: 10.1016/S0140-6736(12)61689-4 . S. Srivastava, T. Anwar, R. Patel, and S. Chauhan, “Dynamics of chronic diseases in metro and non-metro regions of India: evidence from India Human Development Survey I and II,” Int J Sci Rep , vol. 6, no. 8, p. 322, Jul. 2020, doi: 10.18203/issn.2454-2156.IntJSciRep20203116 . S. Srivastava, S. Chauhan, R. Patel, P. Kumar, N. Purkayastha, and S. K. Singh, “Does Change in Family Structure Affect the Household Headship among Older Adults in India? A Gendered Perspective,” Ageing Int , pp. 1–16, Oct. 2020, doi: 10.1007/s12126-020-09401-x . R. Patel, S. P. Marbaniang, S. Srivastava, P. Kumar, S. Chauhan, and D. J. Simon, “Gender differential in low psychological health and low subjective well-being among older adults in India: With special focus on childless older adults,” Plos one , vol. 16, no. 3, p. e0247943, 2021. S. Srivastava et al. , “Older adults’ psychological and subjective well-being as a function of household decision making role: Evidence from cross-sectional survey in India,” Clinical Epidemiology and Global Health , vol. 10, p. 100676, 2021. S. Srivastava, S. Chauhan, and R. Patel, “Socio-economic inequalities in the prevalence of poor self-rated health among older adults in India from 2004 to 2014: A decomposition analysis,” Ageing International , pp. 1–18, 2020. S. T. Ng, N. P. Tey, and M. N. Asadullah, “What matters for life satisfaction among the oldest-old? Evidence from China,” PLOS ONE , vol. 12, no. 2, p. e0171799, Feb. 2017, doi: 10.1371/journal.pone.0171799 . A. M. Fonseca, C. Pal, and I. Martin, “Life satisfaction and quality of life amongst elderly Portuguese living in the community,” Portuguese Journal of Social Science , vol. 7, no. 2, pp. 87–102, Oct. 2008, doi: 10.1386/pjss.7.2.87_1 . H. Koivumaa-Honkanen, R. Honkanen, H. Viinamäki, K. Heikkilä, J. Kaprio, and M. Koskenvuo, “Self-reported Life Satisfaction and 20-Year Mortality in Healthy Finnish Adults,” American Journal of Epidemiology , vol. 152, no. 10, pp. 983–991, Nov. 2000, doi: 10.1093/aje/152.10.983 . S. Ghimire, B. K. Baral, I. Karmacharya, K. Callahan, and S. R. Mishra, “Life satisfaction among elderly patients in Nepal: associations with nutritional and mental well-being,” Health and Quality of Life Outcomes , vol. 16, no. 1, p. 118, Jun. 2018, doi: 10.1186/s12955-018-0947-2 . R. B. Tate, L. Lah, and T. E. Cuddy, “Definition of Successful Aging by Elderly Canadian Males: The Manitoba Follow-Up Study,” The Gerontologist , vol. 43, no. 5, pp. 735–744, Oct. 2003, doi: 10.1093/geront/43.5.735 . J.-Y. An, K. An, L. O’Connor, and S. Wexler, “Life Satisfaction, Self-Esteem, and Perceived Health Status Among Elder Korean Women: Focus on Living Arrangements,” J Transcult Nurs , vol. 19, no. 2, pp. 151–160, Apr. 2008, doi: 10.1177/1043659607313070 . P. Banjare, R. Dwivedi, and J. Pradhan, “Factors associated with the life satisfaction amongst the rural elderly in Odisha, India,” Health Qual Life Outcomes , vol. 13, no. 1, p. 201, Dec. 2015, doi: 10.1186/s12955-015-0398-y . K. M. Bennett, “Psychological wellbeing in later life: The longitudinal effects of marriage, widowhood and marital status change,” International Journal of Geriatric Psychiatry , vol. 20, no. 3, pp. 280–284, 2005. D. Ferring et al. , “Life satisfaction of older people in six European countries: findings from the European Study on Adult Well-Being,” Eur J Ageing , vol. 1, no. 1, pp. 15–25, Dec. 2004, doi: 10.1007/s10433-004-0011-4 . T. Maheswaran and L. Ranjit, “A study on life satisfaction among elderly people,” Research Journal of Sociology , vol. 1, no. 1, pp. 1–8, 2013. F. Subaşı and O. Hayran, “Evaluation of life satisfaction index of the elderly people living in nursing homes,” Archives of Gerontology and Geriatrics , vol. 41, no. 1, pp. 23–29, Jul. 2005, doi: 10.1016/j.archger.2004.10.005 . R. J. Gobbens, “Associations of ADL and IADL disability with physical and mental dimensions of quality of life in people aged 75 years and older,” PeerJ , vol. 6, p. e5425, Aug. 2018, doi: 10.7717/peerj.5425 . Ü. Taş et al. , “Incidence and risk factors of disability in the elderly: The Rotterdam Study,” Preventive Medicine , vol. 44, no. 3, pp. 272–278, Mar. 2007, doi: 10.1016/j.ypmed.2006.11.007 . R. J. J. Gobbens and M. A. L. M. van Assen, “The Prediction of ADL and IADL Disability Using Six Physical Indicators of Frailty: A Longitudinal Study in the Netherlands,” Current Gerontology and Geriatrics Research , vol. 2014, p. e358137, Mar. 2014, doi: 10.1155/2014/358137 . C. O. Akosile, U. G. Mgbeojedo, F. A. Maruf, E. C. Okoye, I. C. Umeonwuka, and A. Ogunniyi, “Depression, functional disability and quality of life among Nigerian older adults: Prevalences and relationships,” Archives of Gerontology and Geriatrics , vol. 74, pp. 39–43, Jan. 2018, doi: 10.1016/j.archger.2017.08.011 . S. Chatterji, J. Byles, D. Cutler, T. Seeman, and E. Verdes, “Health, functioning, and disability in older adults—present status and future implications,” The Lancet , vol. 385, no. 9967, pp. 563–575, Feb. 2015, doi: 10.1016/S0140-6736(14)61462-8 . A. Nagarkar and Y. Kashikar, “Predictors of functional disability with focus on activities of daily living: A community based follow-up study in older adults in India,” Archives of Gerontology and Geriatrics , vol. 69, pp. 151–155, Mar. 2017, doi: 10.1016/j.archger.2016.11.015 . J. D. Nunes et al. , “Functional disability indicators and associated factors in the elderly: a population-based study in Bagé, Rio Grande do Sul, Brazil,” Epidemiol. Serv. Saúde , vol. 26, pp. 295–304, Jun. 2017, doi: 10.5123/s1679-49742017000200007 . D. Serraino, L. Fratino, and V. Zagonel, “Prevalence of functional disability among elderly patients with cancer,” Critical Reviews in Oncology/Hematology , vol. 39, no. 3, pp. 269–273, Sep. 2001, doi: 10.1016/S1040-8428(00)00130-X . Y. Zhong, J. Wang, and S. Nicholas, “Gender, childhood and adult socioeconomic inequalities in functional disability among Chinese older adults,” Int J Equity Health , vol. 16, no. 1, p. 165, Sep. 2017, doi: 10.1186/s12939-017-0662-3 . M. Suzuki, N. Ohyama, K. Yamada, and M. Kanamori, “The relationship between fear of falling, activities of daily living and quality of life among elderly individuals,” Nursing & Health Sciences , vol. 4, no. 4, pp. 155–161, 2002, doi: 10.1046/j.1442-2018.2002.00123.x . F. Y. Beyaztas, G. Kurt, and E. Bolayir, “Life satisfaction level of elderly people: a field study in Sivas, Turkey,” J Pak Med Assoc , vol. 62, no. 3, pp. 221–225, Mar. 2012. J. Karami, A. Sanjabi, and P. Karimi, “The Prediction of Life Satisfaction among the Elderly Based on Resilience and Happiness,” Aging Psychology , vol. 2, no. 4, pp. 229–236, Feb. 2017. T. W. Strine, D. P. Chapman, L. S. Balluz, D. G. Moriarty, and A. H. Mokdad, “The Associations Between Life Satisfaction and Health-related Quality of Life, Chronic Illness, and Health Behaviors among U.S. Community-dwelling Adults,” J Community Health , vol. 33, no. 1, pp. 40–50, Feb. 2008, doi: 10.1007/s10900-007-9066-4 . T. Q. Tran and H. Van Vu, “A microeconometric analysis of housing and life satisfaction among the Vietnamese elderly,” Qual Quant , vol. 52, no. 2, pp. 849–867, Mar. 2018, doi: 10.1007/s11135-017-0492-9 . M. Balachandran, A. S. Raakhee, and H. Sam Sananda Raj, “Life satisfaction and alienation of elderly males and females,” Journal of Indian Academy of Applied Psychology , vol. 33, no. 2, pp. 157–160, 2007. L. Singh and P. K. Singh, “Social network and life satisfaction among older adults in rural Uttar Pradesh, India: an application of structural equation modelling,” J Public Health (Berl.) , vol. 28, no. 5, pp. 491–502, Oct. 2020, doi: 10.1007/s10389-019-01074-4 . IIPS, NPHCE, and MoHFW, “Longitudinal Ageing Study in India (LASI) Wave 1,” International Institute for Population Sciences, Mumbai, India, 2020. Accessed: Jun. 01, 2021. [Online]. Available: https://www.google.com/search?q=International+Institute+for+Population+Sciences+(IIPS)%2C+NPHCE%2C+MoHFW%2C+et+al.+Longitudinal+Ageing+Study+in+India+(LASI)+Wave+1.+Mumbai%2C+India&rlz=1C1CHBF_enIN904IN904&oq=International+Institute+for+Population+Sciences+(IIPS)%2C+NPHCE%2C+MoHFW%2C+et+al.+Longitudinal+Ageing+Study+in+India+(LASI)+Wave+1.+Mumbai%2C+India&aqs=chrome..69i57j69i60.775j0j7&sourceid=chrome&ie=UTF-8 T. Muhammad and S. Srivastava, “Why Rotational Living Is Bad for Older Adults? Evidence from a Cross-Sectional Study in India,” Journal of Population Ageing , pp. 1–18, 2020. S. Srivastava and T. Muhammad, “Violence and associated health outcomes among older adults in India: A gendered perspective,” SSM - Population Health , vol. 12, p. 100702, Dec. 2020, doi: 10.1016/j.ssmph.2020.100702 . S. Srivastava and A. Gill, “Untreated morbidity and treatment-seeking behaviour among the elderly in India: Analysis based on National Sample Survey 2004 and 2014,” SSM - Population Health , vol. 10, p. 100557, Apr. 2020, doi: 10.1016/j.ssmph.2020.100557 . S. Chauhan, T. V. Sekher, P. Kumar, S. Srivastava, and R. Patel, “Prevalence, determinants and socio-economic inequality of early marriage among men in India,” Children and Youth Services Review , vol. 116, p. 105273, Sep. 2020, doi: 10.1016/j.childyouth.2020.105273 . S. Srivastava and S. Kumar, “Does socio-economic inequality exist in micro-nutrients supplementation among children aged 6–59 months in India? Evidence from National Family Health Survey 2005–06 and 2015–16,” BMC Public Health , vol. 21, no. 1, p. 545, Mar. 2021, doi: 10.1186/s12889-021-10601-6 . B. Paswan, S. K. Singh, H. Lhungdim, and C. Shekhar, “National Family Health Survey (NFHS-4),” Mumbai, India, 2017. L. Grilli and C. Rampichini, “Ordered logit model,” Encyclopedia of quality of life and well-being research , pp. 4510–4513, 2014. K. H. Asberg and U. Sonn, “The cumulative structure of personal and instrumental ADL. A study of elderly people in a health service district,” Scand J Rehabil Med , vol. 21, no. 4, pp. 171–177, Jan. 1989. K. S. Markides and H. W. Martin, “A Causal Model of Life Satisfaction Among the Elderly1,” Journal of Gerontology , vol. 34, no. 1, pp. 86–93, Jan. 1979, doi: 10.1093/geronj/34.1.86 . S. Sato, S. Demura, H. Kobayashi, and Y. Nagasawa, “The relationship and its change with aging between ADL and daily life satisfaction characteristics in independent Japanese elderly living at home,” Journal of Physiological Anthropology and Applied Human Science , vol. 21, no. 4, pp. 195–204, 2002. H. Kimm, J. W. Sull, B. Gombojav, S.-W. Yi, and H. Ohrr, “Life satisfaction and mortality in elderly people: The Kangwha Cohort Study,” BMC Public Health , vol. 12, no. 1, p. 54, Jan. 2012, doi: 10.1186/1471-2458-12-54 . H. Imuta, S. Yasumura, M. Fujita, H. Arai, and A. Fukao, “[Homebound elderly in a Japanese community: related factors and change of mobility],” Nihon Koshu Eisei Zasshi , vol. 45, no. 9, pp. 883–892, Sep. 1998. S. Matsuda, Y. Tsutsui, and Y. Takashima, “[Evaluation of factors associated with well-being of elderly in an aged society by analytic hierarchy process analysis],” Nihon Koshu Eisei Zasshi , vol. 45, no. 8, pp. 704–712, Aug. 1998. R. Crevenna and T. E. Dorner, “Association between fulfilling the recommendations for health-enhancing physical activity with (instrumental) activities of daily living in older Austrians,” Wien Klin Wochenschr , vol. 131, no. 11, pp. 265–272, Jun. 2019, doi: 10.1007/s00508-019-1511-8 . S.-Y. Kim and S. R. Sok, “Relationships among the perceived health status, family support and life satisfaction of older Korean adults,” International Journal of Nursing Practice , vol. 18, no. 4, pp. 325–331, 2012, doi: 10.1111/j.1440-172X.2012.02050.x . J. C. Meléndez, J. M. Tomás, A. Oliver, and E. Navarro, “Psychological and physical dimensions explaining life satisfaction among the elderly: A structural model examination,” Archives of Gerontology and Geriatrics , vol. 48, no. 3, pp. 291–295, May 2009, doi: 10.1016/j.archger.2008.02.008 . Y. Pan, S. H. W. Chan, Y. Xu, and K. C. Yeung, “Determinants of life satisfaction and self-perception of ageing among elderly people in China: An exploratory study in comparison between physical and social functioning,” Archives of Gerontology and Geriatrics , vol. 84, p. 103910, Sep. 2019, doi: 10.1016/j.archger.2019.103910 . M. Mather, “The emotion paradox in the aging brain,” Annals of the New York Academy of Sciences , vol. 1251, no. 1, pp. 33–49, 2012, doi: 10.1111/j.1749-6632.2012.06471.x . L. Zhou, J. Lu, G. Chen, L. Dong, and Y. Yao, “Is There a Paradox of Aging: When the Negative Aging Stereotype Meets the Positivity Effect in Older Adults,” Experimental Aging Research , vol. 43, no. 1, pp. 80–93, Jan. 2017, doi: 10.1080/0361073X.2017.1258254 . A. Filus, D. U. Junghaenel, S. Schneider, J. E. Broderick, and A. A. Stone, “Age Effects of Frames of Reference in Self-Reports of Health, Well-Being, Fatigue and Pain,” Applied Research Quality Life , vol. 15, no. 1, pp. 35–54, Mar. 2020, doi: 10.1007/s11482-018-9663-7 . L. Li and J. Liang, “Social exchanges and subjective well-being among older Chinese: Does age make a difference?,” Psychology and Ageing , vol. 22, no. 2, pp. 386–391, 2007. J. Liu, “Research on the Elderly’s Life Satisfaction and the Influence Factors——Analysis Based on National Baseline Data of China Health and Retirement Longitudinal Study(CHARLS),” undefined , 2015, Accessed: Jun. 24, 2021. [Online]. Available: https://www.semanticscholar.org/paper/Research-on-the-Elderly%27s-Life-Satisfaction-and-the-Liu/d95e2ce70be5ee69d928c88b867f77838e126191 Y. Zhou et al. , “Socio-economic factors related with the subjective well-being of the rural elderly people living independently in China,” International Journal for Equity in Health , vol. 14, no. 1, p. 5, Jan. 2015, doi: 10.1186/s12939-015-0136-4 . R. Patel and S. Chauhan, “Gender differential in health care utilisation in India,” Clinical Epidemiology and Global Health , vol. 8, no. 2, pp. 526–530, 2020. N. N. Mudege and A. C. Ezeh, “Gender, aging, poverty and health: Survival strategies of older men and women in Nairobi slums,” Journal of Aging Studies , vol. 23, no. 4, pp. 245–257, Dec. 2009, doi: 10.1016/j.jaging.2007.12.021 . D.-C. Yang, J.-D. Lee, C.-C. Huang, H.-I. Shih, and C.-M. Chang, “Association between multiple geriatric syndromes and life satisfaction in community-dwelling older adults: A nationwide study in Taiwan,” Archives of Gerontology and Geriatrics , vol. 60, no. 3, pp. 437–442, May 2015, doi: 10.1016/j.archger.2015.02.001 . W. Yanfang and W. Xutao, “A multi-factor analysis on the life satisfaction of the elderly and choices of the elderly support patterns in rural areas: Based on the households survey on the left-behind elderly,” China Economic Studies , 2014. D. Heller, D. Watson, and R. Ilies, “The role of person versus situation in life satisfaction: A critical examination.,” Psychological bulletin , vol. 130, no. 4, p. 574, 2004. R. Ilies, J. Yao, P. L. Curseu, and A. X. Liang, “Educated and Happy: A Four-Year Study Explaining the Links Between Education, Job Fit, and Life Satisfaction,” Applied Psychology , vol. 68, no. 1, pp. 150–176, 2019, doi: 10.1111/apps.12158 . J. A. Fernández-Niño, L. J. Bonilla-Tinoco, B. S. Manrique-Espinoza, M. Romero-Martínez, and A. L. Sosa-Ortiz, “Work status, retirement, and depression in older adults: An analysis of six countries based on the Study on Global Ageing and Adult Health (SAGE),” SSM - Population Health , vol. 6, pp. 1–8, Dec. 2018, doi: 10.1016/j.ssmph.2018.07.008 . P.-A. Liao, H.-H. Chang, and L.-C. Sun, “National Health Insurance program and life satisfaction of the elderly,” Aging & Mental Health , vol. 16, no. 8, pp. 983–992, Nov. 2012, doi: 10.1080/13607863.2012.692765 . M. Silverstein, Z. Cong, and S. Li, “Intergenerational Transfers and Living Arrangements of Older People in Rural China: Consequences for Psychological Well-Being,” The Journals of Gerontology: Series B , vol. 61, no. 5, pp. S256–S266, Sep. 2006, doi: 10.1093/geronb/61.5.S256 . W. Zhang and G. Liu, “Childlessness, Psychological Well-being, and Life Satisfaction Among the Elderly in China,” J Cross Cult Gerontol , vol. 22, no. 2, pp. 185–203, Mar. 2007, doi: 10.1007/s10823-007-9037-3 . H. Li, I. Chi, and L. Xu, “Life satisfaction of older Chinese adults living in rural communities,” Journal of cross-cultural gerontology , vol. 28, no. 2, pp. 153–165, 2013. D. J. Deeg and P. A. Bath, “Self-rated health, gender, and mortality in older persons: introduction to a special section,” The Gerontologist , vol. 43, no. 3, pp. 369–371, 2003. R. Ghubach, O. El-Rufaie, T. Zoubeidi, S. Sabri, S. Yousif, and H. F. Moselhy, “Subjective life satisfaction and mental disorders among older adults in UAE in general population,” International Journal of Geriatric Psychiatry: A journal of the psychiatry of late life and allied sciences , vol. 25, no. 5, pp. 458–465, 2010. M. Gutiérrez, J. M. Tomás, L. Galiana, P. Sancho, and M. A. Cebrià, “Predicting life satisfaction of the Angolan elderly: A structural model,” Aging & Mental Health , vol. 17, no. 1, pp. 94–101, 2013. H.-C. Hsu, “Trajectories and covariates of life satisfaction among older adults in Taiwan,” Archives of Gerontology and Geriatrics , vol. 55, no. 1, pp. 210–216, Jul. 2012, doi: 10.1016/j.archger.2011.08.011 . C. Li, I. Chi, X. Zhang, Z. Cheng, L. Zhang, and G. Chen, “Urban and rural factors associated with life satisfaction among older Chinese adults,” Aging & Mental Health , vol. 19, no. 10, pp. 947–954, Oct. 2015, doi: 10.1080/13607863.2014.977767 . Y. Stephan, J. Caudroit, and A. Chalabaev, “Subjective health and memory self-efficacy as mediators in the relation between subjective age and life satisfaction among older adults,” Aging & mental health , vol. 15, no. 4, pp. 428–436, 2011. I. J. Deary et al. , “Age-associated cognitive decline,” Br Med Bull , vol. 92, pp. 135–152, 2009, doi: 10.1093/bmb/ldp033 . N. Schwarz and F. Strack, “Reports of subjective well-being: Judgmental processes and their methodological implications,” Well-being: The foundations of hedonic psychology , vol. 7, pp. 61–84, 1999. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-721491","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":44869821,"identity":"8938d8a4-267f-430a-bc04-0a2009ca9d25","order_by":0,"name":"Shekhar Chauhan","email":"","orcid":"","institution":"International Institute for Population Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shekhar","middleName":"","lastName":"Chauhan","suffix":""},{"id":44869822,"identity":"646446b4-99d2-43d4-9b75-bfea012b286f","order_by":1,"name":"Pradeep Kumar","email":"","orcid":"","institution":"International Institute for Population Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Pradeep","middleName":"","lastName":"Kumar","suffix":""},{"id":44869823,"identity":"2e1861de-c623-4475-a533-27040ae1d5ae","order_by":2,"name":"Shobhit Srivastava","email":"","orcid":"","institution":"International Institute for Population Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shobhit","middleName":"","lastName":"Srivastava","suffix":""},{"id":44869824,"identity":"28c32455-aecd-491f-bcdb-5f0b1119a206","order_by":3,"name":"Ratna Patel","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYFADdh42BoYKIIOZuYGAUmYwKcHADNJyBiTASIoWxjYQm4AW8/bzxx783GFXx8/Me+wx77zaaP52oJYfFdtwapE5k8xu2HsmWUKymS/dmHfb8dwZhxkbGHvO3MapRYIhmU2Ct41ZwuAwj5k077ZjuQ1ALcyMbXi08D9mk/zbVi9hD9Yy51jufIJaJJLZpHnbDksYMIO0NNTkbiCs5bGZtOyZ45IzDvOlSc45diB3I1DLQbx+4U98Jvl2RzU/f3vvMYk3NXW5884fPvjgRwVuLWCAFBGHweQB/OpRtdQRVDwKRsEoGAUjDwAAYxtRTWw1V2IAAAAASUVORK5CYII=","orcid":"","institution":"International Institute for Population Sciences","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ratna","middleName":"","lastName":"Patel","suffix":""}],"badges":[],"createdAt":"2021-07-15 12:29:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-721491/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-721491/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":14097659,"identity":"dff54fe0-36f5-4b0f-815b-d5f2bdb65115","added_by":"auto","created_at":"2021-09-29 07:29:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":603261,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-721491/v1/76b8de13-4e92-47db-b289-56a6d857daa0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eDo Functional Limitations Predict Life Satisfaction Among Older Adults in India: A Study based on LASI Survey in India\u003c/p\u003e","fulltext":[{"header":"Background:","content":"\u003cp\u003eOver the years, India has witnessed an unprecedented growth in population resulting from higher fertility rates across India [1]. However, the decline in fertility rates in recent times has brought down the country's population growth rate [2]. With the declining growth rate in recent years, a new issue on population dynamics has arisen, i.e., the ageing population. A decline in fertility rates coupled with increased life expectancy has led to a rise in ageing population [3]. Improving education, health facilities, and life expectancy has led to an increase in the proportion of the elderly population in India, and the share of the elderly population has increased from 5.3 percent in 1971 to 5.7 percent in 1981 and further from 6 percent in 1991 to 8 percent in 2011 [4]. Moreover, by 2050, the share of the 60\u0026thinsp;+\u0026thinsp;population is projected to climb 19 percent, or approximately 323\u0026nbsp;million people in India [5]. Increasing life expectancy adds more life to years and adds disabilities to the life years among the elderly [6]. The ageing process implies a higher probability of suffering from disease and disability [5], [7].\u003c/p\u003e \u003cp\u003eThe ageing process not only affects the household headship [8] but also has been widely associated with chronic diseases [7], low psychological health [9], [10], low subjective well-being [9], [10], poor self-rated health [11], and life satisfaction [12]. Life satisfaction is an important universal objective and measurement of quality of life [13]. Life satisfaction among the elderly is a critical aspect of the psychological dimension that has proved association with positive health behaviours [14], better physical and mental health outcomes [15], and successful ageing [16]. Moreover, life satisfaction is a general measure of overall wellbeing that measures the degree of coherence between life dreamed of and the life achieved [17]. Various factors have been linked to life satisfaction among the elderly, including social support [18], living arrangement [18], marital status [19], and demographic factors [20]\u0026ndash;[22]. Functional limitations as measured through Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) have also been linked to life satisfaction among the elderly [18].\u003c/p\u003e \u003cp\u003eFunctional limitation/disability is a relevant health outcome to examine the quality of life among the elderly [23]. Disability can be examined in several ways; however, using ADL and IADL to measure disability is one of the most popular and widely used tools [24]. ADL functions are more concerned with an individual\u0026rsquo;s self-care, whereas IADL functions are more concerned with self-reliant functioning in daily life [25]. Studies have noted that ADL disability presents greater difficulties and is a severe form of disability than IADL disability [26], [27]. Several previous studies were conducted examining associated factors of functional limitations in ADL and IADL among the elderly [28]\u0026ndash;[31]. Unfortunately, limited evidence was presented that examined the association between functional limitations and life satisfaction among the elderly [23]. A study in the Nigerian context examined the association between functional disability and quality of life; however, depression was also included as a covariate of quality of life and functional limitations [26]. Another study in Japan contextualized quality of life through ADL; however, the main focus was on the association between fear of falling and quality of life [32].\u003c/p\u003e \u003cp\u003eIn recognition of its importance, research evidence evaluating life satisfaction among older people has increased globally [12], [33]\u0026ndash;[36], but such research is minimalistic in the Indian context. Whatever limited research evaluating life satisfaction among the elderly in India is limited to various community settings [18], [21], [37], [38]. Furthermore, to the author\u0026rsquo;s best knowledge, none of the studies in the Indian context has examined life satisfaction among the elderly population in the context of ADL and IADL. In Indian society, older people are traditionally attended by their family members and are more likely to be satisfied with their lives [18]. During ageing, older people deal with ADL and IADL limitations, and therefore, it becomes seemingly stressful for them to remain satisfied with their life. Given the positive association between life satisfaction and an individual\u0026rsquo;s social support [14], and an inverse relationship between life satisfaction and solitude [33], this study becomes vital as it intends to examine life satisfaction through the lens of functional limitations among the elderly.\u003c/p\u003e \u003cp\u003eGiven the above background, an attempt has been made to explore the association between functional limitations and life satisfaction among the older population in India. The study also explored the association between socioeconomic and demographic characteristics with life satisfaction among the older population. The study hypothesizes that the elderly with ADL and IADL related functional disabilities would have Low Life Satisfaction (LLS), representing it vice-versa. Those without ADL and IADL related functional disabilities would have higher life satisfaction (HLS).\u003c/p\u003e"},{"header":"Methods:","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source:\u003c/h2\u003e \u003cp\u003eData for this study was utilized from the recent release of Longitudinal Ageing Study in India (LASI) wave 1 [39]. The LASI is a nationally representative survey of over 72000 older adults aged 45 and above across India's states and union territories [39]. The survey adopted a three-stage sampling design in rural areas and a four-stage sampling design in urban areas. In each state/UT, the first stage involved the selection of Primary Sampling Units (PSUs), that is, sub-districts (Tehsils/Talukas), and the second stage involved the selection of villages in rural areas and wards in urban areas in the selected PSUs [39]. In rural areas, households were selected from selected villages in the third stage [39]. However, sampling in urban areas involved an additional stage. Specifically, in the third stage, one Census Enumeration Block (CEB) was randomly selected in each urban area [39]. In the fourth stage, households were selected from this CEB [39]. The detailed methodology, with the complete information on the survey design and data collection, was published in the survey report [39]. The present study is conducted on eligible respondents aged 60 years and above. The total sample size for the present study is 31,464 older adults aged 60 years and above. The Indian Council of Medical Research (ICMR) extended the necessary guidance and ethical approval for conducting the LASI [39].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eVariable description\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eOutcome variable\u003c/h2\u003e \u003cp\u003eLife satisfaction among older adults was assessed using the questions a. In most ways, my life is close to ideal; b. The conditions of my life are excellent; c. I am satisfied with my life d. So far, I have got the important things I want in life; e. If I could live my life again, I would change almost nothing. The responses were categorized as strongly disagree, somewhat disagree, slightly disagree, neither agree nor disagree, slightly agree, somewhat agree, and strongly agree. Using the responses to the five statements regarding life satisfaction, a scale was constructed. The categories of the scale are \u0026lsquo;low satisfaction\u0026rsquo; (score of 5\u0026ndash;20), \u0026lsquo;medium satisfaction\u0026rsquo; (score of 21\u0026ndash;25), and \u0026lsquo;high satisfaction\u0026rsquo; (score of 26\u0026ndash;35) [39]. The outcome variable was coded as 0 \u0026ldquo;high,\u0026rdquo; 1 \u0026ldquo;medium,\u0026rdquo; and 2 \u0026ldquo;low.\u0026rdquo;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eControl variable\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eMain control variables\u003c/h2\u003e \u003cp\u003eDifficulty in ADL (Activities of Daily Living) was coded as no and yes. Activities of Daily Living (ADL) is a term used to refer to normal daily self-care activities (such as movement in bed, changing position from sitting to standing, feeding, bathing, dressing, grooming, personal hygiene, etc.) The ability or inability to perform ADLs is used to measure a person\u0026rsquo;s functional status, especially in the case of people with disabilities and older adults [40], [41]. Difficulty in IADL (Instrumental Activities of Daily Living) was coded as no and yes. Instrumental activities of daily living are not necessarily related to the fundamental functioning of a person, but they let an individual live independently in a community. The set ask were necessary for independent functioning in the community. Respondents were asked if they were having any difficulties that were expected to last more than three months, such as preparing a hot meal, shopping for groceries, making a telephone call, taking medications, doing work around the house or garden, managing money (such as paying bills and keeping track of expenses), and getting around or finding an address in unfamiliar places [40], [41].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003eIndividual control variables\u003c/h2\u003e \u003cp\u003eAge was categorized as young old (60\u0026ndash;69 years), old-old (70\u0026ndash;79 years), and oldest-old (80\u0026thinsp;+\u0026thinsp;years) [42]. Sex was coded as male and female. Educational status was categorized as no education/primary not completed, primary, secondary, and higher [42]. Living arrangement was categorized as living alone, living with a spouse, living with children, and living with others. Marital status was categorized as currently married, widowed, and others [42]. Others included separated/divorced/never married. Working status was categorized as currently working, retired, and not working [9]. Active community involvement in life: Respondents were said to be socially engaged if they participate in the following activities. Eat out of house (Restaurant/Hotel); Go to park/beach for relaxing/entertainment; Play cards or indoor games; Play outdoor games/sports/exercise/jog/yoga; Visit relatives /friends; Attend cultural performances /shows/Cinema; Attend religious functions /events such as bhajan/satsang/prayer; Attend political/community/organization group meetings; Read books/newspapers/magazines; Watch television/listen radio and use a computer for e-mail/net surfing etc. If the respondent was involved in any of the above activities, the respondent was defined as socially engaged or involved in the community.\u003c/p\u003e \u003cp\u003eSelf-rated health was coded as good which includes excellent, very good, and good, where as poor includes fair and poor [11]. Psychological distress was coded as low, medium and high. Psychological distress was measured using the following questions a. How often did you have trouble concentrating? b. How often did you feel depressed? c. How often did you feel tired or low in energy? d. How often were you afraid of something? e. How often did you feel you were overall satisfied? f. How often did you feel alone? g. How often were you bothered by things that don\u0026rsquo;t usually bother you? h. How often did you feel that everything you did was an effort? i. How often did you feel hopeful about the future? j. How often did you feel happy? The response was coded as 1. Rarely or never 2. Sometimes 3. Often and 4. Most or all of the time. The response was coded as per the question in binary form 0 \u0026ldquo;Rarely or never/ Sometimes\u0026rdquo; and 1 \u0026ldquo;Often/ Most or all of the time\u0026rdquo; (Cronbach alpha: 0.70) [40].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eHousehold control variables\u003c/h2\u003e \u003cp\u003eThe monthly per-capita consumer expenditure (MPCE) quintile was assessed using household consumption data. Sets of 11 and 29 questions on the expenditures on food and non-food items, respectively, were used to canvas the sample households. Food expenditure was collected based on a reference period of seven days, and non-food expenditure was collected based on reference periods of 30 days and 365 days. Food and non-food expenditures have been standardized to the 30-day reference period. The monthly per capita consumption expenditure (MPCE) is computed and used as the summary measure of consumption. The variable was then divided into five quintiles, i.e., from poorest to richest [39]. Religion was coded as Hindu, Muslim, Christian, and Others. Caste was recoded as Scheduled Tribe, Scheduled Caste, Other Backward Class, and others [43], [44]. The Scheduled Caste includes \u0026ldquo;untouchables,\u0026rdquo;; a group of the population that is socially segregated and financially/economically by their low status as per Hindu caste hierarchy. The Scheduled Castes (SCs) and Scheduled Tribes (STs) are among India's most disadvantaged socio-economic groups. The OBC is the group of people who were identified as \u0026ldquo;educationally, economically and socially backward.\u0026rdquo; The OBC\u0026rsquo;s are considered low in the traditional caste hierarchy but are not considered untouchables. The \u0026ldquo;other\u0026rdquo; caste category is identified as having higher social status [44]. The place of residence was categorized as rural and urban. The region was coded as North, Central, East, Northeast, West, and South [45].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics, along with bivariate analysis, was used to present the preliminary analysis. Apart from that, the ordered logistic regression analysis was used to carve out the results. The dependent variables were ordered as 0 \u0026ldquo;high,\u0026rdquo; 1 \u0026ldquo;medium,\u0026rdquo; and 2 \u0026ldquo;low.\u0026rdquo; The ordered logit model is a regression model for an ordinal response variable. The model is based on the cumulative probabilities of the response variable. In particular, the logit of each cumulative probability is assumed to be a linear function of the covariates with regression coefficients constant across Response Categories [46]. All the methods were performed in accordance with the relevant guidelines and regulations laid down by the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results:","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents socio-economic profile of older adults in India, 2017-18. About one-fourth of older adults were not fully independent for ADL, and nearly half of the older adults were not independent for IADL. More than half of the older adults belonged to the young-old cohort, 68 per cent of older adults had no education/primary not completed, and six per cent of older adults were living alone. Three-fifth of older adults were currently married, nearly one-third of older adults were working, and only nine per cent of older adults had community involvement. About 47 per cent of older adults reported poor self-rated health, and 29 per cent of older adults had high psychological distress. A higher proportion of older adults were Hindu, belonged to the OBC caste group, and lived in rural areas.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-economic profile of older adults in India, 2017-18\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBackground characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty in ADL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23,802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty in IADL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15,334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung-old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18,410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld-old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9,501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOldest-old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14,931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education/primary not completed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21,381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary completed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary completed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiving arrangement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with spouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21,475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19,391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ewidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWorking status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9,680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13,470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCommunity involvement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28,545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSelf-rated health\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14,882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePsychological distress\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12,135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10,216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9,114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMPCE quintile\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25,871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCaste\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScheduled Caste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScheduled Tribe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Backward Class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14,231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22,196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9,268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31,464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the percentage of older adults with high, medium, and low life satisfaction by background characteristics. Overall, about one-third of older adults had low life satisfaction scores, and 46% of older adults had a high life satisfaction score. Difficulty in ADL and IADL had a significant association with life satisfaction among older adults. For example, older adults who were not independent for ADL (37%) and IADL (35%) had a more low life satisfaction score than their counterparts. The low life satisfaction score was higher among older females than older males (33.8% vs. 30.4%). A negative association was observed between low life satisfaction scores and the educational level of older adults. Moreover, older adults who lived alone had more low life satisfaction score (47.8%). A low life satisfaction score was significantly higher among older adults who had community involvement (44.1%) than those who had no community involvement (31%). The low life satisfaction score was higher among older adults who reported poor self-rated health (36.7%) than those who reported good self-rated health (27.9%). Older adults who had high psychological stress reported more low life satisfaction score (47.2%). Similar to education, low life satisfaction scores among older adults had a significant negative association with the MPCE quintile. Low life satisfaction scores were more prevalent among older adults who belonged to scheduled caste/scheduled tribe. Moreover, older adults who lived in rural areas reported higher low life satisfaction scores compared to those who lived in urban areas (34.4% vs. 26.7%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePercentage of older adults with High, Medium and Low life satisfaction by their background characteristics in India, 2017-18\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBackground characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eLife satisfaction\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHigh\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eMedium\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eLow\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty in ADL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty in IADL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.352\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung-old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld-old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOldest-old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education/primary not completed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary completed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary completed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiving arrangement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with spouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ewidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWorking status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCommunity involvement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSelf-rated health\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePsychological distress\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMPCE quintile\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCaste\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScheduled Caste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScheduled Tribe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Backward Class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ep-value based on chi-square test\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEstimates from ordered logistic regression analysis for life satisfaction among older adults are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Model 1 shows unadjusted odds ratio for life satisfaction whereas Model 2 provides the adjusted (odds ratio) estimates for life satisfaction. For older adults who were independent for ADL, the odds of low life satisfaction score (LSS) versus the combined medium and high LSS were 1.20 times more than for older adults who were not independent for ADL [UOR: 1.20; CI: 1.14\u0026ndash;1.26]. Likewise, the odds of combined categories of low and medium LSS versus high LSS was 1.20 times higher for those who were independent for ADL than those who were not independent. However, this result was not significant in adjusted model 2. The odds of difficulty in IADL decreased from unadjusted to adjusted model. For older adults who had difficulty in IADL, the odds of low LSS versus the combined medium and high LSS were 1.13 times higher than for older adults who had not difficulty in IADL [AOR: 1.13; CI: 1.08\u0026ndash;1.19]. Likewise, the odds of combined categories of low and medium LSS versus high LSS was 1.13 times higher for those who had difficulty in IADL than those who did not have. For female, the odds of low LSS versus the combined medium and high LSS were 0.94 times lower than for males. Similarly, the odds of the combined categories of low and medium LSS versus high LSS was 0.94 times lower for females compared to males. For older adults with higher education, the odds of low LSS versus the combined medium and high LSS were 1.31 times higher than for those who had no education. Likewise, the odds of the combined categories of low and medium LSS versus high LSS was 1.31 times higher for older adults with higher education compared to those who had no education. Moreover, for older adults who lived in rural areas, the odds of low LSS versus the combined medium and high LSS were 1.11 times higher than for those who lived in urban areas. Likewise, the odds of the combined categories of low and medium LSS versus high LSS was 1.11 times higher for older adults living in rural areas compared to those who lived in urban areas.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOrdered logistic regression estimates for life satisfaction among older adults in India, 2017-18\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBackground characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel-1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel-2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eUOR (CI)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eAOR (CI)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty in ADL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.20*(1.14,1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98(0.92,1.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty in IADL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41*(1.35,1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13*(1.08,1.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung-old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld-old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93*(0.89,0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOldest-old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81*(0.75,0.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94*(0.89,0.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education/primary not completed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary completed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.94*(1.76,2.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary completed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.60*(1.44,1.79)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.31*(1.18,1.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiving arrangement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.27*(1.10,1.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with spouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90(0.80,1.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86*(0.77,0.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ewidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96(0.91,1.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07(0.93,1.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWorking status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93*(0.88,0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.89*(0.83,0.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCommunity involvement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05(0.97,1.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSelf-rated health\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.32*(1.26,1.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePsychological distress\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.92*(1.82,2.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.99*(2.82,3.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMPCE quintile\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.31*(1.21,1.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13*(1.05,1.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10*(1.02,1.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06(0.98,1.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16*(1.08,1.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93(0.85,1.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95(0.85,1.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCaste\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScheduled Caste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.20*(1.12,1.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScheduled Tribe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.18*(1.09,1.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Backward Class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99(0.93,1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.11*(1.05,1.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01(0.94,1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.35*(1.26,1.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05(0.96,1.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50*(0.46,0.54)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.19*(1.11,1.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e/cut1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.02(-0.05,0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02(0.86,1.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e/cut2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97*(0.94,0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.13*(1.96,2.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eRef: Reference; *if p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; UOR: Unadjusted odds ratio; AOR: Adjusted odds ratio; CI: Confidence interval; Life satisfaction: 0 \"High:, 1 \"medium\" and 2 \"low\".\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion:","content":"\u003cp\u003eBy examining the association between functional disability and life satisfaction among the elderly, this study addressed the long-standing gap in the literature. Previously, minimal literature has examined the association between functional disability and life satisfaction [47]\u0026ndash;[49], and such studies from the Indian context are somewhat more limited [18]. Banjare et al. (2015) examined determinants associated with life satisfaction among the elderly in rural Odisha, and they did not exclusively examine the association between functional limitation and life satisfaction; rather, they included the functional limitation as a general predictor of life satisfaction [18]. Therefore, the current study fills the research gap to a great extent while examining the association between functional disability and life satisfaction among the elderly. The findings noted support for our hypothesis that those with ADL and IADL related functional disabilities would have Low Life Satisfaction (LLS). The unadjusted and adjusted model findings noted higher odds of LLS among elderly with ADL and IADL related functional limitations. These findings agree with previously available literature [18], [50]. Occurrence of functional limitations bound elderly to the home [51], cut their personal ties [52], and limit their physical activity [53], which could be associated with lower life satisfaction among them. Functional limitations reduce the ability to move and reduce participation in social activities and social contacts, leading to a decline in life satisfaction among the elderly.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe odds of LLS were lower among the oldest-old than the young-old elderly, which deviates from the findings of several previous studies\u0026nbsp;[49], [54], [55]. This study specifically noted higher chances of low life satisfaction among young-old than oldest old. Generally, it is assumed that as age increases, the odds of low life satisfaction among the elderly would decrease due to the onset of several chronic conditions and change in living arrangement; however, the findings in this study are somewhat different. A study in the Chinese context corroborated the findings of this study and noted that older individuals had a higher level of life satisfaction than their younger counterparts\u0026nbsp;[56]. The finding of lower odds of LLS among the oldest-old is compatible with a phenomenon known as the paradox of ageing\u0026nbsp;[57], [58]. The paradox of ageing relates to the notion that older people tend to react less to adverse situations, ignore irrelevant negative stimuli better, and remember relatively more positive information than negative information\u0026nbsp;[57], leading to higher life satisfaction. Also, older people are more likely to derive emotional satisfaction from prioritizing positive information processing\u0026nbsp;[58], which could have also linked to higher life satisfaction among the oldest elderly. To add more, a study noted that older people tend to use less interpersonal comparisons than younger people, positively affecting their life satisfaction\u0026nbsp;[59].\u003c/p\u003e\n\u003cp\u003eThe odds of LLS were lower among female elderly than their male counterparts, implying that the satisfaction level was higher among female elderly than in male elderly. Previous studies reported mixed findings where certain studies noted higher life satisfaction among male elderly\u0026nbsp;[60], whereas few other studies noted higher life satisfaction among female elderly\u0026nbsp;[12], [61], [62]. Older women are more likely to seek healthcare in India\u0026nbsp;[63], partially explaining their higher life satisfaction. Furthermore, women enjoy an advantage in adapting to old age complications over men\u0026nbsp;[64], which could also explain the higher life satisfaction among older women than older men.\u003c/p\u003e\n\u003cp\u003eHowever, the odds of LLS were declining with the increase in the educational status of the elderly; this study noted higher odds of LLS for each class of educated elderly than non-educated elderly. In general, education is positively linked to life satisfaction in previous literature\u0026nbsp;[9], [55], [65]. However, quite a few studies noted similar results as in this study\u0026nbsp;[60], [66]. A possible mechanism that links education to job satisfaction and further to life satisfaction may partially explain the higher life satisfaction among educated elderly\u0026nbsp;[67], [68]. It explains that those with higher education would find a job that fits better to their skills and abilities, leading to higher life satisfaction. However, this study noted an otherwise result where odds of LLS were higher among educated elderly. There could be a few plausible mechanisms for the same in this study. First, individuals with lower levels of education may be easily satisfied with their current simple living conditions in contrast to educated elderly still having some unsatisfied needs in their life\u0026nbsp;[56]. Educated elderly might be working before getting retired, and after retirement, they might be feeling a sudden change in their environment and lifestyle, which may partially explain the status of life satisfaction among them. Moreover, pension status after retirement plays an important role in depression among the elderly, which may also partially explain the life satisfaction among the elderly\u0026nbsp;[69]; however, this study did not examine pension status and its association with life satisfaction among the elderly.\u003c/p\u003e\n\u003cp\u003eCorroborating with several previous studies\u0026nbsp;[70]\u0026ndash;[72], this study also noted a higher odds of LLS among elderly living alone and lower odds of LLS among the elderly living with children. Living with children provides a sense of security and social support to the elderly and a sense of belongingness, which could be attributed to higher life satisfaction. Living with children provides social support that improves self-esteem, gives a purpose to live, and can rightly be attributed to higher life satisfaction. Family support has been positively linked to life satisfaction among the elderly\u0026nbsp;[54]. Several research has presented evidence that financial support from children contributes to life satisfaction among the elderly\u0026nbsp;[71], [73]. As expected, those who reported poor self-rated health and had high psychological distress had higher odds of LLS. This finding is in agreement with previously available literature in the Indian context\u0026nbsp;[18], [74]\u0026ndash;[78]. Elderly having poor psychological health are more prone to depression, which could further be linked to LLS\u0026nbsp;[18]. Good health allows the elderly to maintain social contacts, resulting in a higher level of life satisfaction.\u003c/p\u003e\n\u003cp\u003eThe elderly in rural areas had higher odds of LLS, implying a higher life satisfaction among the urban elderly. Previous studies also noted a higher life satisfaction among the urban elderly\u0026nbsp;[78]. The elderly in urban areas have greater access to medical services, which could be linked to higher life satisfaction\u0026nbsp;[72]. Moreover, urban elderly have a greater awareness of their age-related outcomes, which can further be linked to higher life satisfaction\u0026nbsp;[79]. The modern facilities, better infrastructure, and higher pension allowance in urban areas probably contributed to the higher life satisfaction among the urban elderly\u0026nbsp;[12].\u003c/p\u003e\n\u003ch2\u003eLimitations and strengths of the study:\u003c/h2\u003e\n\u003cp\u003eThe study findings should be interpreted in the light of several limitations. One major challenge to perceive the well-being of older adults is to obtain reliable information on self-rated life satisfaction, as some oldest-old and old-old people may be suffering from loss of cognitive ability leading to ambiguity in the study results [80]. To a certain extent, possible biases in self-evaluation of life satisfaction may be driven by socio-economic factors. The cross-sectional nature of data limits our understanding of causality, and reverse causation is possible for study findings. Despite the above limitations, the study has certain noteworthy strengths too. The study is based on recently released data, therefore, providing the current estimates. Furthermore, the study findings can be generalized in a broader context as the data collected are nationally representative. The study measured life satisfaction with various items, therefore providing robust estimates than those studies where life satisfaction was measured with a single item [78]. Measuring life satisfaction with a single item may be influenced by the mood of the respondents during the interview and other situational factors, and therefore measuring life satisfaction with a set of items will always be a suggested way to examine life satisfaction [81]. At last, minimal research investigated the association between functional disability and life satisfaction among the elderly. This study could set things in motion for other researchers who may explore this association in their future studies.\u003c/p\u003e"},{"header":"Conclusion:","content":"\u003cp\u003eIn this study, a possible association between functional limitations and life satisfaction among the elderly was explored, along with exploring other determinants of life satisfaction among the elderly in India using information from a nationally representative survey. Both ADL and IADL were noted as factors determining life satisfaction among elderly and elderly reporting ADL and IADL had higher odds of LLS. Other prominent factors determining life satisfaction among the elderly include higher age, female gender, living with children, good self-rated health, low psychological distress, and urban residence. This study focuses on functional limitations and life satisfaction among the elderly and certainly has some policy suggestions. Addressing psychological distress among the elderly could be a game-changer in providing a sense of satisfaction among the elderly, and to achieve this, there is a need to strengthen the quality of care delivered to older people. The setting up of geriatric clinics under the Primary Health Care services would bring the necessary change as this would provide timely healthcare services to the elderly and generate a perception of overall satisfaction among the elderly as they may feel secure in the presence of better health infrastructure. Since living with children enhances life satisfaction among the elderly, more stress should be laid upon the counseling among the younger generation, which can encourage them to support and look after the needs of their elderly as it would improve further lead to life satisfaction among the elderly [18]. At last, focus needs to be aimed at the elderly who are not independent for ADL and IADL functions and are suffering from severe functional limitations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eADL:\u0026nbsp;\u003c/strong\u003eActivity of Daily Living\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIADL:\u0026nbsp;\u003c/strong\u003eInstrumental Activity of Daily Living\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLASI\u003c/strong\u003e: Longitudinal Ageing Study in India\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCI:\u0026nbsp;\u003c/strong\u003eConfidence Interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUOR:\u0026nbsp;\u003c/strong\u003eUnadjusted Odds Ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOR:\u0026nbsp;\u003c/strong\u003eOdds Ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLLS:\u0026nbsp;\u003c/strong\u003eLow Life Satisfaction\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHLS:\u0026nbsp;\u003c/strong\u003eHigh Life Satisfaction\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe data is freely available on request and survey agencies that conducted the field survey for the data collection have collected a prior consent from the respondent. The ethical clearance was provided by Indian Council of Medical Research (ICMR), India. Moreover, participants were provided with the information brochures explaining the purpose of the survey, ways of protecting their privacy, and safety of the health assessments as part of the ethics protocols.\u003c/p\u003e\n\u003ch2\u003eConsent for publication:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available with the International Institute for Population Sciences, Mumbai, India repository and could be accessed from the following link: https://iipsindia.ac.in/sites/default/files/LASI_DataRequestForm_0.pdf. Those who wish to download the data have to follow the above link. This link leads to a data request form designed by International Institute for Population Sciences. After completing the form, it should be mailed to: \u003ca href=\"mailto:[email protected]\"\[email protected]\u003c/a\u003e for further processing. After successfully sending the mail, individual will receive the data in a reasonable time.\u003c/p\u003e\n\u003ch2\u003eCompeting Interest:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eAuthors did not receive any funding to carry out this research.\u003c/p\u003e\n\u003ch2\u003eAuthor\u0026rsquo;s Contribution:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe concept was drafted by SC and RP. SS and PK contributed to the analysis design. SC advised on the paper and assisted in paper conceptualization. SC and RP contributed in the comprehensive writing of the article. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eP. M. Kulkarni and M. Alagarajan, \u0026ldquo;Population Growth, Fertility, and Religion in India,\u0026rdquo; \u003cem\u003eEconomic and Political Weekly\u003c/em\u003e, vol. 40, no. 5, pp. 403\u0026ndash;410, 2005, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.jstor.org/stable/4416131\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eD. E. Bloom, \u003cem\u003ePopulation Dynamics in India and Implications for Economic Growth\u003c/em\u003e. Oxford University Press, 2012. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/oxfordhb/9780199734580.013.0015\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Chauhan and P. Arokiasamy, \u0026ldquo;India\u0026rsquo;s demographic dividend: state-wise perspective,\u0026rdquo; \u003cem\u003eJournal of Social and Economic Development\u003c/em\u003e, vol. 20, no. 1, pp. 1\u0026ndash;23, 2018.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eR. Patel, S. Chauhan, D. Chaurasiya, S. Kumar, and B. Paswan, \u0026ldquo;Role and Impact of Social Capital on Health of Older Adult in India,\u0026rdquo; \u003cem\u003eIndian Journal of Social Research\u003c/em\u003e, vol. 60, no. 2, pp. 279\u0026ndash;305, 2019.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eA. Agarwal, A. Lubet, E. Mitgang, S. Mohanty, and D. E. Bloom, \u0026ldquo;Population aging in India: Facts, issues, and options,\u0026rdquo; in \u003cem\u003ePopulation change and impacts in Asia and the Pacific\u003c/em\u003e, Springer, 2020, pp. 289\u0026ndash;311.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eC. J. L. Murray \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990\u0026ndash;2010: a systematic analysis for the Global Burden of Disease Study 2010,\u0026rdquo; \u003cem\u003eThe Lancet\u003c/em\u003e, vol. 380, no. 9859, pp. 2197\u0026ndash;2223, Dec. 2012, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(12)61689-4\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Srivastava, T. Anwar, R. Patel, and S. Chauhan, \u0026ldquo;Dynamics of chronic diseases in metro and non-metro regions of India: evidence from India Human Development Survey I and II,\u0026rdquo; \u003cem\u003eInt J Sci Rep\u003c/em\u003e, vol. 6, no. 8, p. 322, Jul. 2020, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.18203/issn.2454-2156.IntJSciRep20203116\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Srivastava, S. Chauhan, R. Patel, P. Kumar, N. Purkayastha, and S. K. Singh, \u0026ldquo;Does Change in Family Structure Affect the Household Headship among Older Adults in India? A Gendered Perspective,\u0026rdquo; \u003cem\u003eAgeing Int\u003c/em\u003e, pp. 1\u0026ndash;16, Oct. 2020, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12126-020-09401-x\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eR. Patel, S. P. Marbaniang, S. Srivastava, P. Kumar, S. Chauhan, and D. J. Simon, \u0026ldquo;Gender differential in low psychological health and low subjective well-being among older adults in India: With special focus on childless older adults,\u0026rdquo; \u003cem\u003ePlos one\u003c/em\u003e, vol. 16, no. 3, p. e0247943, 2021.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Srivastava \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Older adults\u0026rsquo; psychological and subjective well-being as a function of household decision making role: Evidence from cross-sectional survey in India,\u0026rdquo; \u003cem\u003eClinical Epidemiology and Global Health\u003c/em\u003e, vol. 10, p. 100676, 2021.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Srivastava, S. Chauhan, and R. Patel, \u0026ldquo;Socio-economic inequalities in the prevalence of poor self-rated health among older adults in India from 2004 to 2014: A decomposition analysis,\u0026rdquo; \u003cem\u003eAgeing International\u003c/em\u003e, pp. 1\u0026ndash;18, 2020.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. T. Ng, N. P. Tey, and M. N. Asadullah, \u0026ldquo;What matters for life satisfaction among the oldest-old? Evidence from China,\u0026rdquo; \u003cem\u003ePLOS ONE\u003c/em\u003e, vol. 12, no. 2, p. e0171799, Feb. 2017, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0171799\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eA. M. Fonseca, C. Pal, and I. Martin, \u0026ldquo;Life satisfaction and quality of life amongst elderly Portuguese living in the community,\u0026rdquo; \u003cem\u003ePortuguese Journal of Social Science\u003c/em\u003e, vol. 7, no. 2, pp. 87\u0026ndash;102, Oct. 2008, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1386/pjss.7.2.87_1\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eH. Koivumaa-Honkanen, R. Honkanen, H. Viinam\u0026auml;ki, K. Heikkil\u0026auml;, J. Kaprio, and M. Koskenvuo, \u0026ldquo;Self-reported Life Satisfaction and 20-Year Mortality in Healthy Finnish Adults,\u0026rdquo; \u003cem\u003eAmerican Journal of Epidemiology\u003c/em\u003e, vol. 152, no. 10, pp. 983\u0026ndash;991, Nov. 2000, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/aje/152.10.983\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Ghimire, B. K. Baral, I. Karmacharya, K. Callahan, and S. R. Mishra, \u0026ldquo;Life satisfaction among elderly patients in Nepal: associations with nutritional and mental well-being,\u0026rdquo; \u003cem\u003eHealth and Quality of Life Outcomes\u003c/em\u003e, vol. 16, no. 1, p. 118, Jun. 2018, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12955-018-0947-2\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eR. B. Tate, L. Lah, and T. E. Cuddy, \u0026ldquo;Definition of Successful Aging by Elderly Canadian Males: The Manitoba Follow-Up Study,\u0026rdquo; \u003cem\u003eThe Gerontologist\u003c/em\u003e, vol. 43, no. 5, pp. 735\u0026ndash;744, Oct. 2003, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/geront/43.5.735\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eJ.-Y. An, K. An, L. O\u0026rsquo;Connor, and S. Wexler, \u0026ldquo;Life Satisfaction, Self-Esteem, and Perceived Health Status Among Elder Korean Women: Focus on Living Arrangements,\u0026rdquo; \u003cem\u003eJ Transcult Nurs\u003c/em\u003e, vol. 19, no. 2, pp. 151\u0026ndash;160, Apr. 2008, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1043659607313070\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eP. Banjare, R. Dwivedi, and J. Pradhan, \u0026ldquo;Factors associated with the life satisfaction amongst the rural elderly in Odisha, India,\u0026rdquo; \u003cem\u003eHealth Qual Life Outcomes\u003c/em\u003e, vol. 13, no. 1, p. 201, Dec. 2015, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12955-015-0398-y\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eK. M. Bennett, \u0026ldquo;Psychological wellbeing in later life: The longitudinal effects of marriage, widowhood and marital status change,\u0026rdquo; \u003cem\u003eInternational Journal of Geriatric Psychiatry\u003c/em\u003e, vol. 20, no. 3, pp. 280\u0026ndash;284, 2005.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eD. Ferring \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Life satisfaction of older people in six European countries: findings from the European Study on Adult Well-Being,\u0026rdquo; \u003cem\u003eEur J Ageing\u003c/em\u003e, vol. 1, no. 1, pp. 15\u0026ndash;25, Dec. 2004, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10433-004-0011-4\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eT. Maheswaran and L. Ranjit, \u0026ldquo;A study on life satisfaction among elderly people,\u0026rdquo; \u003cem\u003eResearch Journal of Sociology\u003c/em\u003e, vol. 1, no. 1, pp. 1\u0026ndash;8, 2013.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eF. Subaşı and O. Hayran, \u0026ldquo;Evaluation of life satisfaction index of the elderly people living in nursing homes,\u0026rdquo; \u003cem\u003eArchives of Gerontology and Geriatrics\u003c/em\u003e, vol. 41, no. 1, pp. 23\u0026ndash;29, Jul. 2005, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.archger.2004.10.005\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eR. J. Gobbens, \u0026ldquo;Associations of ADL and IADL disability with physical and mental dimensions of quality of life in people aged 75 years and older,\u0026rdquo; \u003cem\u003ePeerJ\u003c/em\u003e, vol. 6, p. e5425, Aug. 2018, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7717/peerj.5425\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003e\u0026Uuml;. Taş \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Incidence and risk factors of disability in the elderly: The Rotterdam Study,\u0026rdquo; \u003cem\u003ePreventive Medicine\u003c/em\u003e, vol. 44, no. 3, pp. 272\u0026ndash;278, Mar. 2007, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ypmed.2006.11.007\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eR. J. J. Gobbens and M. A. L. M. van Assen, \u0026ldquo;The Prediction of ADL and IADL Disability Using Six Physical Indicators of Frailty: A Longitudinal Study in the Netherlands,\u0026rdquo; \u003cem\u003eCurrent Gerontology and Geriatrics Research\u003c/em\u003e, vol. 2014, p. e358137, Mar. 2014, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2014/358137\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eC. O. Akosile, U. G. Mgbeojedo, F. A. Maruf, E. C. Okoye, I. C. Umeonwuka, and A. Ogunniyi, \u0026ldquo;Depression, functional disability and quality of life among Nigerian older adults: Prevalences and relationships,\u0026rdquo; \u003cem\u003eArchives of Gerontology and Geriatrics\u003c/em\u003e, vol. 74, pp. 39\u0026ndash;43, Jan. 2018, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.archger.2017.08.011\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Chatterji, J. Byles, D. Cutler, T. Seeman, and E. Verdes, \u0026ldquo;Health, functioning, and disability in older adults\u0026mdash;present status and future implications,\u0026rdquo; \u003cem\u003eThe Lancet\u003c/em\u003e, vol. 385, no. 9967, pp. 563\u0026ndash;575, Feb. 2015, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(14)61462-8\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eA. Nagarkar and Y. Kashikar, \u0026ldquo;Predictors of functional disability with focus on activities of daily living: A community based follow-up study in older adults in India,\u0026rdquo; \u003cem\u003eArchives of Gerontology and Geriatrics\u003c/em\u003e, vol. 69, pp. 151\u0026ndash;155, Mar. 2017, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.archger.2016.11.015\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eJ. D. Nunes \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Functional disability indicators and associated factors in the elderly: a population-based study in Bag\u0026eacute;, Rio Grande do Sul, Brazil,\u0026rdquo; \u003cem\u003eEpidemiol. Serv. Sa\u0026uacute;de\u003c/em\u003e, vol. 26, pp. 295\u0026ndash;304, Jun. 2017, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5123/s1679-49742017000200007\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eD. Serraino, L. Fratino, and V. Zagonel, \u0026ldquo;Prevalence of functional disability among elderly patients with cancer,\u0026rdquo; \u003cem\u003eCritical Reviews in Oncology/Hematology\u003c/em\u003e, vol. 39, no. 3, pp. 269\u0026ndash;273, Sep. 2001, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S1040-8428(00)00130-X\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eY. Zhong, J. Wang, and S. Nicholas, \u0026ldquo;Gender, childhood and adult socioeconomic inequalities in functional disability among Chinese older adults,\u0026rdquo; \u003cem\u003eInt J Equity Health\u003c/em\u003e, vol. 16, no. 1, p. 165, Sep. 2017, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12939-017-0662-3\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eM. Suzuki, N. Ohyama, K. Yamada, and M. Kanamori, \u0026ldquo;The relationship between fear of falling, activities of daily living and quality of life among elderly individuals,\u0026rdquo; \u003cem\u003eNursing \u0026amp; Health Sciences\u003c/em\u003e, vol. 4, no. 4, pp. 155\u0026ndash;161, 2002, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1046/j.1442-2018.2002.00123.x\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eF. Y. Beyaztas, G. Kurt, and E. Bolayir, \u0026ldquo;Life satisfaction level of elderly people: a field study in Sivas, Turkey,\u0026rdquo; \u003cem\u003eJ Pak Med Assoc\u003c/em\u003e, vol. 62, no. 3, pp. 221\u0026ndash;225, Mar. 2012.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eJ. Karami, A. Sanjabi, and P. Karimi, \u0026ldquo;The Prediction of Life Satisfaction among the Elderly Based on Resilience and Happiness,\u0026rdquo; \u003cem\u003eAging Psychology\u003c/em\u003e, vol. 2, no. 4, pp. 229\u0026ndash;236, Feb. 2017.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eT. W. Strine, D. P. Chapman, L. S. Balluz, D. G. Moriarty, and A. H. Mokdad, \u0026ldquo;The Associations Between Life Satisfaction and Health-related Quality of Life, Chronic Illness, and Health Behaviors among U.S. Community-dwelling Adults,\u0026rdquo; \u003cem\u003eJ Community Health\u003c/em\u003e, vol. 33, no. 1, pp. 40\u0026ndash;50, Feb. 2008, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10900-007-9066-4\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eT. Q. Tran and H. Van Vu, \u0026ldquo;A microeconometric analysis of housing and life satisfaction among the Vietnamese elderly,\u0026rdquo; \u003cem\u003eQual Quant\u003c/em\u003e, vol. 52, no. 2, pp. 849\u0026ndash;867, Mar. 2018, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11135-017-0492-9\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eM. Balachandran, A. S. Raakhee, and H. Sam Sananda Raj, \u0026ldquo;Life satisfaction and alienation of elderly males and females,\u0026rdquo; \u003cem\u003eJournal of Indian Academy of Applied Psychology\u003c/em\u003e, vol. 33, no. 2, pp. 157\u0026ndash;160, 2007.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eL. Singh and P. K. Singh, \u0026ldquo;Social network and life satisfaction among older adults in rural Uttar Pradesh, India: an application of structural equation modelling,\u0026rdquo; \u003cem\u003eJ Public Health (Berl.)\u003c/em\u003e, vol. 28, no. 5, pp. 491\u0026ndash;502, Oct. 2020, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10389-019-01074-4\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eIIPS, NPHCE, and MoHFW, \u0026ldquo;Longitudinal Ageing Study in India (LASI) Wave 1,\u0026rdquo; International Institute for Population Sciences, Mumbai, India, 2020. Accessed: Jun. 01, 2021. [Online]. Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.google.com/search?q=International+Institute+for+Population+Sciences+(IIPS)%2C+NPHCE%2C+MoHFW%2C+et+al.+Longitudinal+Ageing+Study+in+India+(LASI)+Wave+1.+Mumbai%2C+India\u0026amp;rlz=1C1CHBF_enIN904IN904\u0026amp;oq=International+Institute+for+Population+Sciences+(IIPS)%2C+NPHCE%2C+MoHFW%2C+et+al.+Longitudinal+Ageing+Study+in+India+(LASI)+Wave+1.+Mumbai%2C+India\u0026amp;aqs=chrome..69i57j69i60.775j0j7\u0026amp;sourceid=chrome\u0026amp;ie=UTF-8\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eT. Muhammad and S. Srivastava, \u0026ldquo;Why Rotational Living Is Bad for Older Adults? Evidence from a Cross-Sectional Study in India,\u0026rdquo; \u003cem\u003eJournal of Population Ageing\u003c/em\u003e, pp. 1\u0026ndash;18, 2020.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Srivastava and T. Muhammad, \u0026ldquo;Violence and associated health outcomes among older adults in India: A gendered perspective,\u0026rdquo; \u003cem\u003eSSM - Population Health\u003c/em\u003e, vol. 12, p. 100702, Dec. 2020, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ssmph.2020.100702\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Srivastava and A. Gill, \u0026ldquo;Untreated morbidity and treatment-seeking behaviour among the elderly in India: Analysis based on National Sample Survey 2004 and 2014,\u0026rdquo; \u003cem\u003eSSM - Population Health\u003c/em\u003e, vol. 10, p. 100557, Apr. 2020, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ssmph.2020.100557\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Chauhan, T. V. Sekher, P. Kumar, S. Srivastava, and R. Patel, \u0026ldquo;Prevalence, determinants and socio-economic inequality of early marriage among men in India,\u0026rdquo; \u003cem\u003eChildren and Youth Services Review\u003c/em\u003e, vol. 116, p. 105273, Sep. 2020, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.childyouth.2020.105273\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Srivastava and S. Kumar, \u0026ldquo;Does socio-economic inequality exist in micro-nutrients supplementation among children aged 6\u0026ndash;59 months in India? Evidence from National Family Health Survey 2005\u0026ndash;06 and 2015\u0026ndash;16,\u0026rdquo; \u003cem\u003eBMC Public Health\u003c/em\u003e, vol. 21, no. 1, p. 545, Mar. 2021, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12889-021-10601-6\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eB. Paswan, S. K. Singh, H. Lhungdim, and C. Shekhar, \u0026ldquo;National Family Health Survey (NFHS-4),\u0026rdquo; Mumbai, India, 2017.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eL. Grilli and C. Rampichini, \u0026ldquo;Ordered logit model,\u0026rdquo; \u003cem\u003eEncyclopedia of quality of life and well-being research\u003c/em\u003e, pp. 4510\u0026ndash;4513, 2014.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eK. H. Asberg and U. Sonn, \u0026ldquo;The cumulative structure of personal and instrumental ADL. A study of elderly people in a health service district,\u0026rdquo; \u003cem\u003eScand J Rehabil Med\u003c/em\u003e, vol. 21, no. 4, pp. 171\u0026ndash;177, Jan. 1989.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eK. S. Markides and H. W. Martin, \u0026ldquo;A Causal Model of Life Satisfaction Among the Elderly1,\u0026rdquo; \u003cem\u003eJournal of Gerontology\u003c/em\u003e, vol. 34, no. 1, pp. 86\u0026ndash;93, Jan. 1979, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/geronj/34.1.86\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Sato, S. Demura, H. Kobayashi, and Y. Nagasawa, \u0026ldquo;The relationship and its change with aging between ADL and daily life satisfaction characteristics in independent Japanese elderly living at home,\u0026rdquo; \u003cem\u003eJournal of Physiological Anthropology and Applied Human Science\u003c/em\u003e, vol. 21, no. 4, pp. 195\u0026ndash;204, 2002.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eH. Kimm, J. W. Sull, B. Gombojav, S.-W. Yi, and H. Ohrr, \u0026ldquo;Life satisfaction and mortality in elderly people: The Kangwha Cohort Study,\u0026rdquo; \u003cem\u003eBMC Public Health\u003c/em\u003e, vol. 12, no. 1, p. 54, Jan. 2012, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1471-2458-12-54\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eH. Imuta, S. Yasumura, M. Fujita, H. Arai, and A. Fukao, \u0026ldquo;[Homebound elderly in a Japanese community: related factors and change of mobility],\u0026rdquo; \u003cem\u003eNihon Koshu Eisei Zasshi\u003c/em\u003e, vol. 45, no. 9, pp. 883\u0026ndash;892, Sep. 1998.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS. Matsuda, Y. Tsutsui, and Y. Takashima, \u0026ldquo;[Evaluation of factors associated with well-being of elderly in an aged society by analytic hierarchy process analysis],\u0026rdquo; \u003cem\u003eNihon Koshu Eisei Zasshi\u003c/em\u003e, vol. 45, no. 8, pp. 704\u0026ndash;712, Aug. 1998.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eR. Crevenna and T. E. Dorner, \u0026ldquo;Association between fulfilling the recommendations for health-enhancing physical activity with (instrumental) activities of daily living in older Austrians,\u0026rdquo; \u003cem\u003eWien Klin Wochenschr\u003c/em\u003e, vol. 131, no. 11, pp. 265\u0026ndash;272, Jun. 2019, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00508-019-1511-8\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eS.-Y. Kim and S. R. Sok, \u0026ldquo;Relationships among the perceived health status, family support and life satisfaction of older Korean adults,\u0026rdquo; \u003cem\u003eInternational Journal of Nursing Practice\u003c/em\u003e, vol. 18, no. 4, pp. 325\u0026ndash;331, 2012, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1440-172X.2012.02050.x\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eJ. C. Mel\u0026eacute;ndez, J. M. Tom\u0026aacute;s, A. Oliver, and E. Navarro, \u0026ldquo;Psychological and physical dimensions explaining life satisfaction among the elderly: A structural model examination,\u0026rdquo; \u003cem\u003eArchives of Gerontology and Geriatrics\u003c/em\u003e, vol. 48, no. 3, pp. 291\u0026ndash;295, May 2009, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.archger.2008.02.008\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eY. Pan, S. H. W. Chan, Y. Xu, and K. C. Yeung, \u0026ldquo;Determinants of life satisfaction and self-perception of ageing among elderly people in China: An exploratory study in comparison between physical and social functioning,\u0026rdquo; \u003cem\u003eArchives of Gerontology and Geriatrics\u003c/em\u003e, vol. 84, p. 103910, Sep. 2019, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.archger.2019.103910\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eM. Mather, \u0026ldquo;The emotion paradox in the aging brain,\u0026rdquo; \u003cem\u003eAnnals of the New York Academy of Sciences\u003c/em\u003e, vol. 1251, no. 1, pp. 33\u0026ndash;49, 2012, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1749-6632.2012.06471.x\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eL. Zhou, J. Lu, G. Chen, L. Dong, and Y. Yao, \u0026ldquo;Is There a Paradox of Aging: When the Negative Aging Stereotype Meets the Positivity Effect in Older Adults,\u0026rdquo; \u003cem\u003eExperimental Aging Research\u003c/em\u003e, vol. 43, no. 1, pp. 80\u0026ndash;93, Jan. 2017, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/0361073X.2017.1258254\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eA. Filus, D. U. Junghaenel, S. Schneider, J. E. Broderick, and A. A. Stone, \u0026ldquo;Age Effects of Frames of Reference in Self-Reports of Health, Well-Being, Fatigue and Pain,\u0026rdquo; \u003cem\u003eApplied Research Quality Life\u003c/em\u003e, vol. 15, no. 1, pp. 35\u0026ndash;54, Mar. 2020, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11482-018-9663-7\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eL. Li and J. Liang, \u0026ldquo;Social exchanges and subjective well-being among older Chinese: Does age make a difference?,\u0026rdquo; \u003cem\u003ePsychology and Ageing\u003c/em\u003e, vol. 22, no. 2, pp. 386\u0026ndash;391, 2007.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eJ. Liu, \u0026ldquo;Research on the Elderly\u0026rsquo;s Life Satisfaction and the Influence Factors\u0026mdash;\u0026mdash;Analysis Based on National Baseline Data of China Health and Retirement Longitudinal Study(CHARLS),\u0026rdquo; \u003cem\u003eundefined\u003c/em\u003e, 2015, Accessed: Jun. 24, 2021. [Online]. Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.semanticscholar.org/paper/Research-on-the-Elderly%27s-Life-Satisfaction-and-the-Liu/d95e2ce70be5ee69d928c88b867f77838e126191\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eY. Zhou \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Socio-economic factors related with the subjective well-being of the rural elderly people living independently in China,\u0026rdquo; \u003cem\u003eInternational Journal for Equity in Health\u003c/em\u003e, vol. 14, no. 1, p. 5, Jan. 2015, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12939-015-0136-4\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eR. Patel and S. Chauhan, \u0026ldquo;Gender differential in health care utilisation in India,\u0026rdquo; \u003cem\u003eClinical Epidemiology and Global Health\u003c/em\u003e, vol. 8, no. 2, pp. 526\u0026ndash;530, 2020.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eN. N. Mudege and A. C. Ezeh, \u0026ldquo;Gender, aging, poverty and health: Survival strategies of older men and women in Nairobi slums,\u0026rdquo; \u003cem\u003eJournal of Aging Studies\u003c/em\u003e, vol. 23, no. 4, pp. 245\u0026ndash;257, Dec. 2009, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jaging.2007.12.021\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eD.-C. Yang, J.-D. Lee, C.-C. Huang, H.-I. Shih, and C.-M. Chang, \u0026ldquo;Association between multiple geriatric syndromes and life satisfaction in community-dwelling older adults: A nationwide study in Taiwan,\u0026rdquo; \u003cem\u003eArchives of Gerontology and Geriatrics\u003c/em\u003e, vol. 60, no. 3, pp. 437\u0026ndash;442, May 2015, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.archger.2015.02.001\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eW. Yanfang and W. Xutao, \u0026ldquo;A multi-factor analysis on the life satisfaction of the elderly and choices of the elderly support patterns in rural areas: Based on the households survey on the left-behind elderly,\u0026rdquo; \u003cem\u003eChina Economic Studies\u003c/em\u003e, 2014.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eD. Heller, D. Watson, and R. Ilies, \u0026ldquo;The role of person versus situation in life satisfaction: A critical examination.,\u0026rdquo; \u003cem\u003ePsychological bulletin\u003c/em\u003e, vol. 130, no. 4, p. 574, 2004.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eR. Ilies, J. Yao, P. L. Curseu, and A. X. Liang, \u0026ldquo;Educated and Happy: A Four-Year Study Explaining the Links Between Education, Job Fit, and Life Satisfaction,\u0026rdquo; \u003cem\u003eApplied Psychology\u003c/em\u003e, vol. 68, no. 1, pp. 150\u0026ndash;176, 2019, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/apps.12158\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eJ. A. Fern\u0026aacute;ndez-Ni\u0026ntilde;o, L. J. Bonilla-Tinoco, B. S. Manrique-Espinoza, M. Romero-Mart\u0026iacute;nez, and A. L. Sosa-Ortiz, \u0026ldquo;Work status, retirement, and depression in older adults: An analysis of six countries based on the Study on Global Ageing and Adult Health (SAGE),\u0026rdquo; \u003cem\u003eSSM - Population Health\u003c/em\u003e, vol. 6, pp. 1\u0026ndash;8, Dec. 2018, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ssmph.2018.07.008\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eP.-A. Liao, H.-H. Chang, and L.-C. Sun, \u0026ldquo;National Health Insurance program and life satisfaction of the elderly,\u0026rdquo; \u003cem\u003eAging \u0026amp; Mental Health\u003c/em\u003e, vol. 16, no. 8, pp. 983\u0026ndash;992, Nov. 2012, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13607863.2012.692765\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eM. Silverstein, Z. Cong, and S. Li, \u0026ldquo;Intergenerational Transfers and Living Arrangements of Older People in Rural China: Consequences for Psychological Well-Being,\u0026rdquo; \u003cem\u003eThe Journals of Gerontology: Series B\u003c/em\u003e, vol. 61, no. 5, pp. S256\u0026ndash;S266, Sep. 2006, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/geronb/61.5.S256\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eW. Zhang and G. Liu, \u0026ldquo;Childlessness, Psychological Well-being, and Life Satisfaction Among the Elderly in China,\u0026rdquo; \u003cem\u003eJ Cross Cult Gerontol\u003c/em\u003e, vol. 22, no. 2, pp. 185\u0026ndash;203, Mar. 2007, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10823-007-9037-3\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eH. Li, I. Chi, and L. Xu, \u0026ldquo;Life satisfaction of older Chinese adults living in rural communities,\u0026rdquo; \u003cem\u003eJournal of cross-cultural gerontology\u003c/em\u003e, vol. 28, no. 2, pp. 153\u0026ndash;165, 2013.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eD. J. Deeg and P. A. Bath, \u0026ldquo;Self-rated health, gender, and mortality in older persons: introduction to a special section,\u0026rdquo; \u003cem\u003eThe Gerontologist\u003c/em\u003e, vol. 43, no. 3, pp. 369\u0026ndash;371, 2003.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eR. Ghubach, O. El-Rufaie, T. Zoubeidi, S. Sabri, S. Yousif, and H. F. Moselhy, \u0026ldquo;Subjective life satisfaction and mental disorders among older adults in UAE in general population,\u0026rdquo; \u003cem\u003eInternational Journal of Geriatric Psychiatry: A journal of the psychiatry of late life and allied sciences\u003c/em\u003e, vol. 25, no. 5, pp. 458\u0026ndash;465, 2010.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eM. Guti\u0026eacute;rrez, J. M. Tom\u0026aacute;s, L. Galiana, P. Sancho, and M. A. Cebri\u0026agrave;, \u0026ldquo;Predicting life satisfaction of the Angolan elderly: A structural model,\u0026rdquo; \u003cem\u003eAging \u0026amp; Mental Health\u003c/em\u003e, vol. 17, no. 1, pp. 94\u0026ndash;101, 2013.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eH.-C. Hsu, \u0026ldquo;Trajectories and covariates of life satisfaction among older adults in Taiwan,\u0026rdquo; \u003cem\u003eArchives of Gerontology and Geriatrics\u003c/em\u003e, vol. 55, no. 1, pp. 210\u0026ndash;216, Jul. 2012, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.archger.2011.08.011\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eC. Li, I. Chi, X. Zhang, Z. Cheng, L. Zhang, and G. Chen, \u0026ldquo;Urban and rural factors associated with life satisfaction among older Chinese adults,\u0026rdquo; \u003cem\u003eAging \u0026amp; Mental Health\u003c/em\u003e, vol. 19, no. 10, pp. 947\u0026ndash;954, Oct. 2015, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13607863.2014.977767\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eY. Stephan, J. Caudroit, and A. Chalabaev, \u0026ldquo;Subjective health and memory self-efficacy as mediators in the relation between subjective age and life satisfaction among older adults,\u0026rdquo; \u003cem\u003eAging \u0026amp; mental health\u003c/em\u003e, vol. 15, no. 4, pp. 428\u0026ndash;436, 2011.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eI. J. Deary \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Age-associated cognitive decline,\u0026rdquo; \u003cem\u003eBr Med Bull\u003c/em\u003e, vol. 92, pp. 135\u0026ndash;152, 2009, doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/bmb/ldp033\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eN. Schwarz and F. Strack, \u0026ldquo;Reports of subjective well-being: Judgmental processes and their methodological implications,\u0026rdquo; \u003cem\u003eWell-being: The foundations of hedonic psychology\u003c/em\u003e, vol. 7, pp. 61\u0026ndash;84, 1999.\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Functional limitations, ADL, IADL, Older people, India","lastPublishedDoi":"10.21203/rs.3.rs-721491/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-721491/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eFunctional limitation is a relevant health outcome to examine the quality of life among the elderly. In recognition of its importance, research evidence evaluating life satisfaction among older people has increased globally, but such research is minimalistic in the Indian context. Furthermore studies in the Indian context examining life satisfaction among the elderly population in the context of ADL and IADL are hard to find. Therefore, this study examines the association between functional limitations and life satisfaction among the older population in India.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eData for this study was utilized from the recent release of Longitudinal Ageing Study in India (LASI) wave 1. The total sample size for the present study is 31,464 older adults aged 60 years and above.\u0026nbsp;Life satisfaction was the main dependent variable categorized as 0 “high,” 1 “medium,” and 2 “low.” Descriptive statistics, along with bivariate analysis, was used to present the preliminary analysis. Apart from that, the ordered logistic regression analysis was used to carve out the results. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOverall, about one-third of older adults had low life satisfaction scores, and 46% of older adults had a high life satisfaction score. The low life satisfaction score was higher among older adults who reported poor self-rated health (36.7%) than those who reported good self-rated health (27.9%). For older adults who were independent for ADL, the odds of low life satisfaction score (LSS) versus the combined medium and high LSS were 1.20 times more than for older adults who were not independent for ADL [UOR: 1.20; CI: 1.14-1.26].\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eIn this study, a possible association between functional limitations and life satisfaction among the elderly was explored. Both ADL and IADL were noted as factors determining life satisfaction among elderly and elderly reporting ADL and IADL had higher odds of LLS. The setting up of geriatric clinics under the Primary Health Care services would bring the necessary change as this would provide timely healthcare services to the elderly and generate a perception of overall satisfaction among the elderly as they may feel secure in the presence of better health infrastructure.\u003c/p\u003e","manuscriptTitle":"Do Functional Limitations Predict Life Satisfaction Among Older Adults in India: A Study based on LASI Survey in India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-08-11 13:38:08","doi":"10.21203/rs.3.rs-721491/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"720dc5ee-a898-4ffa-bf61-dd64fb443b6b","owner":[],"postedDate":"August 11th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":6370804,"name":"Geriatrics \u0026 Gerontology"}],"tags":[],"updatedAt":"2021-09-29T07:29:06+00:00","versionOfRecord":[],"versionCreatedAt":"2021-08-11 13:38:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-721491","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-721491","identity":"rs-721491","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}